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Investing and Valuation Lessons from the Renaissance

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I just got back a few days ago from a two-week family holiday in Italy, where we spent the bulk of the second week in Florence, which we used as a springboard to see Tuscany. I kept away from work through much of the period, though I did check my emails once in a while and even tried answering a few on my iPhone, where my awful typing skills restricted me to one-sentence responses. So, if you were one of those people that I responded to, I apologize if I seemed brusque. That said, I am also afflicted with a disease of seeing connections between everything I see around me and investing, and this vacation was no exception. Thus, in Florence, as I gazed at Brunelleschi’s magnificent Duomo on the Cathedral and marveled at the beauty of Michelangelo’s David, I could not help but think about how much we (as investors) can learn from those renaissance geniuses.


The Story of Brunelleschi’s Dome
If you have visited Florence or even read about the dome on its cathedral, I am sure that you have heard its story. The construction of the cathedral was begun in 1296 and continued in fits and starts through much of the next few decades with the Plague bringing it to a standstill in the second half of the fourteenth century. The centerpiece of the cathedral was to be its freestanding dome, but since architects of the age lacked the capacity to build one large enough to cover the church, it was left for another generation to complete. In 1418, two goldsmiths in Florence, Lorenzo Ghiberti and Filippo Brunelleschi, competed in a contest for designing the dome, with Brunelleschi winning by a hair. Brunelleschi spent time studying the Pantheon in Rome, a concrete dome built more than a thousand years prior, but one where all records of its construction had long been destroyed. He started work on his Duomo in 1420 and completed it by 1436, and the result speaks for itself:


Brunelleschi was an artist, skilled in its many forms, but to build the dome, he not only drew on science but actively used it to solve practical problems. To allow the huge dome to stay standing without visible supports, Brunelleschi came up with the ingenious concept of a dome within a dome (a double shell) and stone ribs designed to defend against the spreading created by the weight of the dome. He had to construct hoisting machines to lift the almost four million bricks and large stones and structural innovations to let workers complete the construct. The dome, once completed, was as much an engineering feat as it was an artistic triumph and it remains so today.

Investing and Valuation Lessons
I can think of at least three big lessons that investors can learn from the Renaissance masters. The first is the meaning of faith, a scarce resource in today's markets, as we eagerly seek confirmation that we are right in market movements and are quick to give up, when things don't go our way. The second is the need for humility, an acceptance that much of what we claim to be new and innovative in investing is neither, and that we can learn from looking at the past. The third is that just as the best of the Renaissance required a melding of art and science, the best of investing is built on a combination of story telling and number crunching. 

Lesson 1: The Importance of Faith
Investing is as much about faith as it is about mechanics. As our access to data and models increases, I will borrow words that Tom Friedman used in a different context, and argue that the investing world is becoming flatter. It is not getting any easier to make money from investing and one reason may be that we have no faith in either our ability to attach values to companies, in the face of uncertainty, or in the market’s capacity to correct its mistakes. As a consequence, even those investors who are well versed in valuation mechanics are generally unwilling to act on the valuations that they generate, or when they do, to hold on to them in the face of adversity.  Like many of you, I find myself getting impatient when the stock price does not correct quickly towards my estimated value on my investments and growing uncertain with my own judgment, if the divergence persists for months. As I looked up at the Florence skyline and pondered the patience of those who were willing to build a church first and then wait almost a hundred for someone to come along with its dome, I understood the meaning of faith and how far I have to go to get there.

Lesson 2: There are no new investment lessons, just old ones to relearn
With superior resources and better investment education, we tend to think that we are not only more sophisticated than investors in prior generations but less likely to make the same errors in judgment. If only that were true! Just as the skills that allowed the Romans to build the Pantheon were forgotten for a thousand years and had to be rediscovered by Brunelleschi, there are simple lessons that investors learned in past markets that we seem to forget in new markets. Each time we make collective mistakes as investors and there is a market correction, we are quick to say "never again" only to repeat the same mistakes a few years later. 

Lesson 3: Art and Science
Are you an artist or a scientist? An engineer or a poet? We live in an age where we are asked to pick sides and told that the two cannot co-exist. In the context of valuation, the battle is fought out between the story tellers and the number crunchers, with each claiming the high ground. In the last few years, I have argued not just for a truce between the two sides but also for more engagement,  a marriage of numbers and narrative in valuation and investing. Even my best efforts pale in comparison to one look at Brunelleschi’s dome, since he understood that there was no divide between art and science. It is a lesson that we seem to have forgotten over time, as we force people to choose sides in a battle where there are no winners.

An Investment Renaissance
We live in an age of specialists, and in investments, this has taken the form of experts who operate in silos, option traders who act as if their derivative securities can exist without their underlying assets, fixed income investors who function as if bonds are the only game in town and equity investors who can only talk about stocks. This specialization comes with consequences and one of them is that we tend to operate in echo chambers, talking to people who think like us, act like us and not surprisingly, agree with us. If the words "Renaissance man (or woman)" are used to describe someone whose expertise spans different subject areas, in the context of investing, I would use those words to refer to those investors who can move with ease across markets and are just as comfortable with stories as they are with numbers. This is my subjective judgment but I think that there used to be more of them three decades ago, when I started in investing, and they seem to become rarer by the day.  In corporations, banks, money management units, consulting firms and even in academia, we could use more Renaissance thinking.

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The Ride Sharing Business: Is a Bar Mitzvah moment approaching?

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I did a series of three posts on the ride sharing business about a year ago, starting with a valuation of Uber, moving on to an assessment of Lyft, continuing with a global comparison of ride sharing companies and ending with a discussion of the future of the ride sharing business. In the last of those four posts, I looked at the ride sharing business model, argued that it was unsustainable as currently structured and laid our four possible ways in which it could be evolve: a winner-take-all, a losing game, collusion and a new player (from outside). While ride sharing continues its inexorable advance into new markets and new customers, the last few months has also brought a flurry of game-changing actions, culminating with Uber’s decision about a week ago to abandon China to arch-rival Didi Chuxing. It is a good time to take a look at the market again and perhaps map out where it stands now and what the future holds for it.

The Face of Disruption
While there is much to debate about the future of the ride sharing business, there are a few facts that are no longer debatable. 
  1. Ride sharing continues on its growth path: Ride sharing has grown faster, gone to more places and is used by more people than most people thought it would be able to, even a couple of years ago. The pace of growth is also picking up. Uber took six years before it reached a billion rides in December of 2015, but it took only six months for the company to get to two billion rides. For just the US, the number of users of ride sharing services is estimated to have increased from 8.2 million in 2014 to 20.4 million in 2020. 
    YearNumber of US ride sharers (in millions)% of US adult population
    2014
    8.20
    3.40%
    2015
    12.40
    5.00%
    2016
    15.00
    6.00%
    2017
    17.00
    6.70%
    2018
    18.20
    7.10%
    2019
    19.40
    7.50%
    2020
    20.40
    7.80%
  2. It is globalizing fast: In the same vein, ride sharing which started as a San Francisco experiment that grew into a US business has become global in just a short period, with Asia emerging as the epicenter for future growth. Didi Chuang, the Chinese ridesharing company, completed 1.43 billion rides just in 2015 and it now claims to have 250 million users in 360 Chinese cities. Ride sharing is also acquiring deep roots in both India and Malaysia, and is making advances in Europe and Latin America, despite regulatory pushback. 
  3. Expanding choices: The choices in ride sharing are becoming wider, to attract an even larger audience, from carpooling and private bus services to attract mass transit customers to luxury options for more upscale customers. In addition, ride sharing companies are experimenting with pre-scheduled rides and multiple stops on single trip gain to meet customer needs. 
  4. Devastating the status quo: All of this growth has been devastating for the status quo. Even hardliners in the taxicab and old time car service businesses recognize that ride sharing is not going away and that the ways of doing business have to change. The price of a New York city medallion which was in excess of $1.5 million before the advent of ride sharing continues its plunge, dropping to less than $500,000 in March 2016. The price of a Chicago cab medallion, which peaked at $357,000 in 2013, had dropped to $60,000 by July 2016.
In short, there is no question that the car service business as we know it has been disrupted and that there is no going back to the old days. If you own a taxi cab or a car service business, the question is no longer whether you will lose business to ride sharing companies but how quickly, even with the regulatory authorities standing in as your defenders.

A Flawed Business Model
Disruption is easy but making money off disruption is difficult, and ride sharing companies would be exhibit 1 to back up the proposition. While the ride sharing option is here to stay and will continue to grow, ride sharing companies still have not figured out a way to convert ride sharing revenues in profits. In making this statement, though, I am relying on dribs and drabs of information that are coming out of the existing ride sharing companies, almost all of whom are private. Piecing together the information that we are getting from these unofficial and often selective leaked information, here is what seems clear:
  1. Raising capital at a hefty pace: In the last two years, the ride sharing companies have been active in raising capital, with Uber leading the way and Didi Chuxing close behding. In the graph below, I list the capital raised collectively by players in the ride sharing business over the last three years and the pricing attached to each company in its most recent capital round.
  2. Ride Sharing Company
    Amount Raised in last 12 months (in millions)
    Investor
    Company Priced at (in millions)
    Didi
    $7,300.00
    Apple, Alibaba, Softbank & Others
    $28,000
    Uber
    $3,500.00
    Saudi Arabian Sovereign Fund
    $62,500
    Lyft
    $500.00
    GM
    $5,500
    Ola
    $500.00
    Didi & Existing Investors
    $5,000
    Grabtaxi
    $350.00
    Didi & CIC
    $1,800
    Gett
    $300.00
    Volkswagen
    $2,000
    Via
    $100.00
    VC
    NA
    Scoop
    $5.10
    BMW
    NA
  3. At rich prices: As the table above indicates, the investors who are putting money in the ride sharing companies are willing to pay hefty prices for their holdings, with no signs of a significant pullback (yet). Uber, at its current pricing, is being priced higher than Ford or GM. Note that I use the word “pricing” to indicate what investors are attaching as numbers to these companies because I don’t believe that they have the interest or the stomach to actually value them. If you are confused about the contrast between “value” and “price”, please see my blog post on the topic.
  4. From unconventional capital providers: The capital coming into ride sharing companies is not coming less from the traditional providers to private businesses and more from public investors (Mutual funds, pension funds, wealth management arms of investment banks and sovereign funds). The reasons for the shift are simple on both sides. Public investors want to be invested in the ride sharing companies because they have visions of public offerings at much higher prices and are afraid to be left on the side lines, if that happens. The ride sharing companies are for it because some of them (Uber and Didi, in particular) are getting too big for venture capitalists to capitalize and perhaps because public investors are imposing less onerous constraints on them for providing capital.
  5. While burning through cash quickly: As quickly as the capital is being raised at ride sharing companies, it is being spent at astonishing rates. Uber admitted that it burned through more than a billion dollars in cash in 2015, with a significant portion of that coming from its attempts to increase market share in China. Its competitors are matching it, with Lyft estimated to be burning through about $50 million in cash each month ($600 million over a year) and Didi Chuting's CEO, Jean Liu, openly admitting that â€œWe wouldn’t be here today if it wasn’t for burning cash”. 
The cash burn at ride sharing companies, by itself, is neither uncommon nor, by itself, troubling After all, to grow, you have to spend money, and a young start up often loses money because of infrastructure investments and fixed costs, and as revenues climb, margins should improve and reinvestment should scale down (at least on a proportional basis). The problem with ride sharing is companies in this business are losing money only partially because of their high growth. In fact, I believe that a significant portion of their expenses are associating with maintaining revenues rather than growing them (ride sharing discounts, driver deals and customer deals). I am afraid that I cannot back up that statement with anything more tangible than news stories about ride sharing wars for drivers, big discounts for customers and the leaked statistics from the ride sharing companies.  In effect, it looks like the business model that has brought these companies as far as they have in such a short time period are flawed, because what allowed these companies to grow incredibly fast is getting in the way of converting revenues to profits, since there are no moats to defend.

If you are skeptical about my contention, here is a simple test of whether the cash burn is just a consequence of going for high growth or symptomatic of a business model problem. Assume that the growth ends in the ride sharing business tomorrow and that the ride sharing companies were to compete for existing riders. Do you think that the pieces are in place for these companies to generate profits? I don't think so, as ride prices keep dropping, new ride sharing businesses pop up and the costs continue to increase. 

The Bar Mitzvah Moment
In a post in November 2014 on Twitter’s struggles, I argued that every young growth company has a bar mitzvah moment, a time in its history when markets shift their attention away from surface measures of growth (number of users, in the case of Twitter) to more operating substance (evidence that the users are being monetized). I also argued that to get through these bar mitzvah moments successfully, young growth companies have to be managed on two levels, delivering the conventional metrics on one level while working on creating a business model to convert these metrics into more conventional measures of business success (revenues and earnings) on the other.

This may be premature but I have sense that the bar mitzvah moment has arrived or will be arriving soon for ride sharing companies. After an initial life, where investors have been easily sated with reports of more ridesharing usage (number of cities served, rides, drivers etc.), these investors are starting to ask the tough questions about how ride sharing companies propose turning these impressive usage statistics into profits. What’s driving investor uneasiness?

  • The first factor is that the public investors who have put their money into the ride sharing companies operate under shorter time horizons than many VC investors and the fact that an IPO is not imminent in any of these companies adds to their impatience to see tangible results. 
  • The second factor is that the belief that there will be a winner-take-all, who can then proceed to charge what the market will bear, has receded, as all of the players in the market continue to attract capital. 
  • The third factor is that the possibility that big players like Apple and Google will enter the market is becoming a plausibility and perhaps even a probability and their technological edge and deep pockets could put existing ride sharing companies at a disadvantage.
In my view, it is this perception that change is coming that is leading the flurry of activity that we have seen at ride sharing companies in the last few months. In conventional business terms, the ride sharing companies are trying to shore up their business models, generate pathways to profitability and build competitive advantages. Broadly speaking, these efforts include the following:
  1. Increased Switching costs: The ride sharing companies are working on ways to increase the costs of switching to their competitors, both among drivers (who I described in a prior post as uncontracted free agents) and customers. Uber’s partnership with Toyota, where Toyota will lease cars on favorable terms to Uber drivers, will benefit drivers but will also bind them more closely to Uber, and make it more difficult for them to threaten to go to Lyft for a few thousand dollars. GM’s agreement with Lyft is not as specific but seems to be directed at the same objective. 
  2. Cooperation/Collusion: In my ride sharing post in October 2015, I raised the possibility that the ride sharing companies would follow the route of the Mafia in the United States in the middle of the last century, where crime families divided the US into fiefdoms and agreed not to invade each other’s turf. Uber’s decision to abandon the Chinese market to Didi in return for a 20% ownership stake in that company, in particular, seems to be designed to accomplish this no-compete objective. Uber’s China move specifically seems to be designed to stop the mutually assured destruction that a free-for-all fight with Didi will create. 
  3. Higher Capital Intensity: Though there is little that is tangible that I can point to in support of this notion, I think that the ride sharing companies now recognize that their absence of tangible assets and infrastructure investment can now operate as an impediment to building a sustainable business. Consequently, I will not be surprised to see more investment by the ride sharing companies in self-driving cars, robots and other infrastructure as part of the phase of building up business moats.
As we witness the breakneck pace of change in the ride sharing business, the big question if you are considering investing in these companies is whether these actions will work in laying the groundwork for profitability. Well, yes and no. If the ride sharing business were frozen to include only the current players, it is probable that they will come to an uneasy agreement that will allow them to generate profits. The problem, though, is that the existing structure of this business is anything but settled, with new ride sharing options popping up and large technology companies rumored to be on the cusp of jumping in. The unquestioned winners in the ride sharing game are car service customers, who have seen their car service costs go down while getting more care service options. . 

Uber: An updated valuation
In September 2015, I valued Uber at $23.4 billion, based upon my reading of the market then. In assessing this value, I incorporated what I saw as Uber’s strengths (its reach globally and across many different businesses) and its weaknesses (an out-of-control cost structure and the elimination of many of the insurance and regulatory loopholes that allowed ride sharing to gain such an advantage over conventional car service).  In the last year, as I see it, here is how the fundamental story has been impacted by developments in the last year: 

  1. Revenues: Uber’s growth continues, measured in cities and rides, though the rate of growth has started to slow down, not surprising given its size. Its decision to leave China, the largest ride sharing market in the world, even if it was the right one from the perspective of saving itself from a cash war, will reduce its potential revenues in the future.
  2. Competition: Before you over react to Uber's exit from China, there is good news in that decision. First,by removing the costs associated with going after the China market from the equation, it reduces the problem of cash burn, at least for the near future. Second, its peace treaty with Didi Chuxing puts the smaller players at risk. Lyft, Ola and Grabtaxi, all companies that Didi invested in to stop the Uber juggernaut, may now be left exposed to competition. Third, in return for its decision to leave the China market, Uber does get a 20% stake in Didi Chuxing.
  3. Costs: On the cost front, the ride sharing business continued to evolve, with most of the changes signaling higher costs for the ride sharing companies in the future. Seattle's decision to let Uber/Lyft drivers unionize may be the precursor of similar developments in other cities and higher costs for both companies. On the legal front, cities continue to throw up roadblocks for the ride sharing companies. Uber and Lyft abandoned Austin, after the city passed an ordinance requiring drivers for both services to pass background checks. One symptom of these higher costs is in the leaked financials from Uber, which suggested that the company lost more than a billion dollars in the first half of 2015. 
  4.  Imminent competition: The Silicon Valley gossip continues about Apple and Google preparing to enter the ride sharing market, with Google announcing that it has entered into a partnership with Fiat and that a top robocist had left the self-driving car unit a few days ago. Never one to hide in the shadows, Elon Musk added car sharing to his long list of to dos at Tesla in his Master Plan for the company. It seems clear that while the timing of the change remains up in the air, change is coming to this business.
None of the changes are dramatic but tweaking my valuation to reflect those changes, as well as changes in the macro environment in the last year, my updated valuation for Uber is $28 billion, a little higher than my estimate last year of $23.4 billion. The loss of the China market reduces the total market size but it is offset by a higher market share of the remaining market and a 20% stake in Didi Chuxing. The pricing attached to this Didi stake is $7 billion, but since the same forces that have elevated Uber's pricing are at play across the ride sharing market, I have attached a value of $5 billion to the stake. The picture of the valuation is below:
Download spreadsheet
Clearly, the Saudi Sovereign fund, Goldman Sachs and Fidelity would disagree with me, since their estimated pricing for Uber is more than double my value. They could very well be right in their judgment and I could be wrong, but my valuation reflects my story about the company, which is perhaps not as expansive nor as optimistic as the stories that they might be telling.

What's next?
The ride sharing business is in a state of flux and the next few months will bring more experimentation on the part of companies. Some of these experiments will be with the services offered but more of them will be attempts to get business models that work at converting riders to profits. The ride sharing companies have clearly won the first phase of the disruption battle with the taxicab and car service companies and have been rewarded with high pricing and plentiful capital. The next phase will separate the winners from the losers song the ride sharing companies and it is definitely not going to be boring.

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Last year's posts on ride sharing
  1. On the Uber Rollercoaster: Narrative Tweaks, Twists and Turns
  2. Dream Big or Stay Focused? The Lyft Answer!
  3. The Future of Ride Sharing: Playing Pundit

Uber Valuations
  1. June 2014
  2. September 2015
  3. August 2016

The Bonfire of Venture Capital: The Good, Bad and Ugly Side of Cash Burn!

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In my last post on Uber, I noted that it was burning through cash and that this cash burn, by itself, is neither unexpected nor a bad sign. Since I got quite a few comments on what I said, I decided to make this post just about the causes and consequences of cash burn. In the process, I hope to dispel two myths held on opposite ends of the investing spectrum, the notion on the part of value investors, that a high cash burn signals a death spiral for a business and the equally strongly held belief, at the start-up investing end , that a cash burn is a sign of growth and vitality. 

Cash Burn: The what?
Since it is cash burn, not earnings burn, that concerns us, let’s start with the obvious. It is cash flow, not earnings, that is at the heart of a cash burn problem. While many money losing companies have cash burn problems, not all cash burn problems are money losing, and not all money losing companies have a cash burn problem. To understand cash burn, you have to start with a working definition of cash flows and my definition hews closely to what I use in the context of valuing businesses. The free cash flow to the firm is the cash left over after taxes have been paid and reinvestment needs (to maintain existing assets and generate future growth) have been met:

For mature, going concerns, the after-tax operating income and free cash flow to the firm will be positive (at least on average) and that cash flow is used to service debt payments as well as to provide cash flows to equity in the form of dividends and stock buybacks. Any remaining cash flow, after debt payments and dividends/buybacks, augments the cash balance of the company.

But what if the free cash flow to the firm is negative? That can happen either because a company has operating losses or because it has large reinvestment needs or both occur in tandem. If you have negative free cash flow to the firm, you can draw down an existing cash balance to cover that need and if that turns out to be insufficient, you will have to raise fresh capital, either in the form of new debt or new equity. If this negative cash flow is occasional and is interspersed with positive cash flows in other years, as is often the case with cyclical or commodity companies, you consider it to be a reflection of normal operations of the firm and it should cause few issues in valuation. If, on the other hand, a business has negative cash flows year in and year out, it is said to be burning through cash or having a “cash burn” problem.

To measure the magnitude of the cash spending problem, analysts use a variety of measures. One is to compute the dollar cash spent in a time period, usually a month, and that is termed the Cash Burn rate. Another is to compute the Cash Runway, the time period that it will take for a company to run through its existing cash balance. Thus, a firm with a $1 billion cash balance and a negative cash flow of -$500 million a year has a 2-year Cash Runway. In contrast, another company with a $1 billion cash balance and a negative cash flow of -$ 2 billion a year has only a 6-month Cash Runway. 

Cash Burn: The Why?
Looking at the definition of cash flows should give you a quick sense of why you get high cash burn values (and ratios) at some companies. If your company is and has been losing money or generating very small earnings for an extended period and it sees high growth potential in the future (and invests accordingly), your cash flows will reflect that reality. 

That combination of low operating income/operating losses and high reinvestment is what you should expect to see at many young companies and the resulting negative free cash flow to the firm will be the norm rather than the aberration. As the companies move through the life cycle, the benign perspective on cash burn is that this will cease to be a problem.

As the company scales up, its operating income and margins should increase and as growth starts to scale down (in future years), the reinvestment should start dropping. 

Cash Burn: The what next?
The combination of higher operating margins and lower reinvestment should generate a cross over point where cash flows turn positive and these positive cash flow will carry the value. Rather than talking in abstractions, let me use the numbers in my August 2016 Uber valuation to illustrate. The story that I am telling in these numbers is of a going concern and success, with high revenue growth accompanied by improving operating margins as the first leg, followed by declining growth (and reinvestment) converting negative cash flows to positive cash flows in the second leg and a steady state of high earnings and cash flows reflected in a going concern value in the final phase.
In my Uber forecasts, the cash flows are negative for the first six years, with losses in the first five years adding on to reinvestment in those years. The cash flows turn positive in year 7, just as growth starts to slow and accelerate in the final years of the forecasts.  Though these numbers are specific to Uber, the pattern of cash flows that you see in this figure is typical of the good cash burn story.

The life cycle story that I have laid out is the benign one, where after its start-up pains, a young company turns the corner, starts generating profits and ultimately turns cash flows around. Before you buy into the fairy talk that I have told you, you should consider a more malignant version of this story. In this one, the firm starts off as a growth firm with negative margins and high reinvestment (and cash burn). As the revenues increase over time and the company scales up, the cost structure continues to spiral out-of-control and the margins become more negative over time, rather than less. In fact, with reinvestment creating an additional drain on the cash flows, your free cash flow will be negative for extended and very long time periods and you are on the pathway to venture capital hell. To illustrate what the cash flows would look like in this malignant version of cash burn, I revisited the Uber valuation and changed two numbers. I reduced the operating margin (targeted for year 10) from 20% down to 5% (making ride sharing a commoditized business) and increased reinvestment to match a typical US company (by setting the sales to capital ratio to two, instead of three). The effects on the cash flows are dramatic.
The cash flows stay negative over the next ten years. In this scenario, it is very unlikely that Uber will make it to year 10 or even year 5, as capital providers will balk at feeding the cash burn machine?

So, when is cash burn likely to be value destructive or fatal? If the company operates in a market place, where competition keeps pushing product prices down and the costs of delivering these products continue to rise, it is already on a course to report bigger and bigger losses, even before considering reinvestment. If this company reinvests for growth and the product market conditions do not change (i.e., price cutting and rising costs are expected to continue), it is likely that the reinvestment will not deliver the earnings required to justify that investment. Here, there is no light at the end of the tunnel, as negative cash flows will generally become more negative over time and even when they do turn positive, will be insufficient to cover the burden of negative cash flows in earlier time periods.

Cash Burn: So what?
Though stories about young companies and their cash burn problems abound, there are few that try to make the connection between cash burn and value other than to point to it as a survival risk. To make the connection more explicit, it is worth thinking about why and how cash burn affects the value of an enterprise. 
  1. Dilution Effect: A company has to raise cash to burn through it and if that cash is raised from fresh equity, as it inevitably has to be for young growth companies, the existing owners of the business will have to give up some of their ownership of the company. If you are an equity investor, the greater the cash burn in a company, the less of the company you will end up owning, even if it survives and prospers.
  2. Growth Effect: The dilution effect presumes that there are capital providers who will be supply the cash needed to keep the firm going through its cash burn days, but what if that presumption is incorrect? The best case scenario for the firm, when capital dries up, is that it is able to rein in discretionary spending (which will include all reinvestment for growth) until capital becomes available again. In the meantime, though, the company will have to scale back its growth plans.
  3. Distress Effect: The more dangerous consequence of capital drying up for a young firm with negative free cash flows Is that the firm’s survival is put at risk. This will be the case if the company is unable to meet its operating cash flow needs, even after cutting discretionary capital spending to zero. In this scenario, the firm will have to liquidate itself and given its standing, it will have to settle for a fraction of its value as a going concern.
In intrinsic valuation, both of these effects can and should be captured in your intrinsic value. 
  1. The dilution effect manifests itself as negative cash flows in the early years and a drop in the present value of cash flows. For instance, in my Uber valuation, the present value of the expected cash flows for the first seven years, all negative, is $4.4 billion. While the positive cash flows thereafter more than compensate for this, I am in effect reducing the value of Uber by about 20% for these negative cash flows and this reduction can be viewed as a preemptive discounting of my equity stake in the company for future dilution.
  2. When I discount the negative cash flows back to today and assume that Uber has no chance of game-ending failure, I am assuming that Uber has and will continue to have access to capital, partly because of its size and partly because existing investors have too much to lose if the company goes into death throes. If you believe these assumptions to be too optimistic, you can adjust the valuation in two ways. The first is by putting a cap on how much new capital the firm can raise each year, which will also operate as a constraint on future growth. The other is by allowing for a probability that the firm will fail, either because capital markets shut down or cash flows are more negative than expected. In my Lyft valuation in September 2015, for instance, I allowed for a 10% probability of this occurring and assumed that equity investors would get close to nothing if it did, effectively reducing my valuation today.
In pricing, how does it show up? In a young company, pricing usually involves forecasting revenues or earnings in a future time period, applying a multiple, at which you believe the company will be priced by a potential buyer or the market in an IPO, to these revenues and pricing and then discounting back that end price to today using a target rate of return.

As you can see, there is no explicit adjustment for cash burn in this equation. While you could bring in the effect of negative cash flows, just as you did in intrinsic valuation, by discounting them back to today and netting out against the pricing, doing that removes one of the biggest reasons why investors and analysts like pricing, which is that it is simple. The only adjustment mechanism left is the target rate of return and, in my view, it becomes the mechanism that venture capitalists and investors use to deal with cash burn concerns. Given that these target rates of return also carry the weight of reflecting failure risk, it should come as no surprise that VC target rates of return for investment look high (at 30%, 40% or even 50%) relative to rates used for established companies.

An Investor Checklist for Cash Burn
If you are an investor in a company, public or private, that is burning through cash, you may be wondering at this point what you would look at to determine whether a company’s cash burn is benign or malignant and whether it is on a glide path to glory or a Hari Kari mission. Here are some things to consider:
  1. Understand why the company is burning through cash: Looking back at the constituents of free cash flows, there are multiple paths that can lead to negative free cash flows. The most benign scenario is one where a money making company reports negative cash flows because of large reinvestment. Not only is this negative cash flow a down payment for future growth but it is also discretionary, insofar as managers can scale back reinvestment if capital becomes scarce. The most dangerous combination is a money losing company that reinvests very little, since there is little potential for a growth payoff and management will be helpless if capital freezes up.
  2. Diagnose the operating business: While there is often a lot of noise around the numbers, you still have to make your best judgments about the profitability of the underlying business. In particular, you want to focus on the pricing power that your company has and the economies of scale in its cost structure. The most benign scenario on this dimension is one where the company has significant pricing power and a cost structure that benefits from scale, allowing for margin improvement over time.
  3. Gauge management skills: Managing a cash-burning company does require management to keep costs under control, while reinvesting to generate growth and to take care of short term cash flow problems, while mapping out a long term strategy. The best case scenario for investors is that the company is run by a management team that works within the cash flow constraints of today while mapping out pathways to profitability over time. The worst case scenario is that the company is managed by those who view negative cash flows as a badge of honor and a sign of growth rather than a temporary problem to overcome.
  4. Growth/Reinvestment trade off: Since reinvesting for future growth can be a big reason for negative cash flows, to assess the payoff in value terms, you have to both estimate how much growth will be created and its value effect. In its most value-creating form, reinvestment will generate high growth coupled with high returns and its most value-destructive form, reinvestment will drain cash flows while generating low growth and poor profits.
  5. Capital Market A firm with a cash burn problem is more depending upon capital markets for its survival, since a closing of these markets may be sufficient to put the firm into receivership. It is no surprise, therefore, that cash burning companies that have larger cash balances or more established capital providers are viewed more positively than cash burning companies that have less cash and have less access to capital.
This checklist requires subjective judgments along the way and you will be wrong sometimes, in spite of your best efforts. That should not stop you from trying.

The Bottom Line
If you are an investor in a company that is burning through cash, don't panic! If your investments are in young companies, it is exactly what you should expect to see though you should do your due diligence, examining the reasons for the cash burn in and the soundness of the underlying business model. If you are an old-time value investor, weaned on large dividends, positive cash flows and margin of safety, you may find yourself avoiding companies that have these cash burn problems but be glad that there are investors who are less risk averse than you are and willing to bet on these companies.

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Posts on valuing young companies

  1. Blood in the Shark Tank: Pre-money, Post-money and Play-money Valuations
  2. Billion Dollar Tech Babies: A Blessing of Unicorns or a Parcel of Hogs
  3. The Bonfire of Venture Capital: The Good, Bad and Ugly Side of Cash Burn

Superman and Stocks: It's not the Cape (CAPE), it's the Kryptonite(Cash flow)!

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Just about a week ago, I was on a 13-hour plane trip from Tokyo to New York. I know that this will sound strange but I like long flights for two reasons. The first is that they give me extended stretches of time when I can work without interruption, no knocks on the door or email or phone calls. I readied my lecture notes for next semester and reviewed and edited a manuscript for one of my books in the first half on the trip. The second is that I can go on movie binges with my remaining time, watching movies that I would have neither the time nor the patience to watch otherwise. On this trip, however, I made the bad decision of watching Batman versus Superman, Dawn of Justice, a movie so bad that the only way that I was able to get through it was by letting my mind wander, a practice that I indulge in frequently and without apologies or guilt. I pondered whether Superman needed his suit or more importantly, his cape, to fly. After all, his powers come from his origins (that he was born in Krypton) and not from his outfit and the cape seems to be more of an aerodynamic drag than an augmentation. These deep thoughts about Superman's cape then led me to thinking about CAPE, the variant on PE ratios that Robert Shiller developed, and how many articles I have read over the last decade that have used this measure as the basis for warning me that stocks are headed for a fall. Finally, I started thinking about Kryptonite, the substance that renders Superman helpless, and what would be analogous to it in the stock market. I did tell you that I have a wandering mind and so, if you don't like Superman or stocks, consider yourself forewarned!

The Stock Market’s CAPE
As stocks hit one high after another, the stock market looks like Superman, soaring to new highs and possessed of super powers.

There are many who warn us that stocks are overheating and that a fall is imminent. Some of this worrying is natural, given the market's rise over the last few years, but there are a few who seem to have surrendered entirely to the notion that stocks are in a bubble and that there is no rational explanation for why investors would invest in them. In a post from a couple of years ago, I titled these people as  bubblers and classified them into doomsday, knee jerk, conspiratorial, righteous and rational bubblers. The last group (rational bubblers) are generally sensible people, who having fallen in love with a market metric, are unable to distance themselves from it.

One of the primary weapons that rational bubblers use to back up their case is the Cyclically Adjusted Price Earnings (CAPE), a measure developed and popularized by Robert Shiller, Nobel prize winner whose soothsaying credentials were amplified by his calls on the dot com and housing bubbles. For those who don’t quite grasp what the CAPE is, it is the conventional PE ratio for stocks, with two adjustments to the earnings. First, instead of using the most recent year’s earnings, it is computed as the average earnings over the prior ten years. Second, to allow for the effects of inflation, the earnings in prior years is adjusted for inflation.  The CAPE case against stocks is a simple one to make and it is best seen by graphing Shiller’s version of it over time.
Shiller CAPE data (from his site)
The current CAPE of 27.27 is well above the historic average of 16.06 and if you buy into the notion of mean reversion, the case makes itself, right? Not quite! As you can see, even within the CAPE story, there are holes, largely depending upon what time period you use for your averaging. Relative to the fully history, the CAPE looks high today, but relative to the last 20 years, the story is much weaker. Contrary to popular view, mean reversion is very much in the eyes of the beholder.

The CAPE’s Weakest Links
Robert Shiller has been a force in finance, forcing us to look at the consequences of investor behavior and chronicling the consequences of “irrational exuberance”. His work with Karl Case in developing a real estate index that is now widely followed has introduced discipline and accountability into real estate investing and his historical data series on stocks, which he so generously shares with us, is invaluable. You can almost see the “but” coming and I will not disappoint you. Of all of his creations, I find CAPE to be not only the least compelling but also potentially the most dangerous, in terms of how often it can lead investors astray. So, at the risk of angering those of you who are CAPE followers, here is my case against putting too much faith in this measure, with much of it representing updates of what my post from two years ago.
1. The CAPE is not that informative
The notion that CAPE is a significant improvement on conventional PE is based on the two adjustments that it makes, first by replacing earnings in the most recent period with average earnings over ten years and the second by adjusting past earnings for inflation to make them comparable to current earnings. Both adjustments make intuitive sense but at least in the context of the overall market, I am not sure that either adjustment makes much of a difference. In the graph below, I show the trailing PE, normalized PE (using the average earnings over the last ten years) and CAPE for the S&P 500 from 1969 to 2016 (last twelve months). I also show Shiller's CAPE, which is based on a broader group of US stocks in the same graph.
Download spreadsheet with PE ratios
First, it is true that especially after boom periods (where earnings peak) or economic crises (where trailing earnings collapse), the CAPEs (both mine and Shiller's) yield different numbers than PE.  Second, and more important, the four measures move together most of the time, with the correlation matrix shown in the figure. Note that the correlation is close to one between the normalized PE and the CAPE, suggesting that the inflation adjustment does little or nothing in markets like the US and even the normalization makes only a marginal difference with a correlation of 0.86 between the unadjusted PE and the Shiller PE.

2. The CAPE is not that predictive
The question then becomes whether using the CAPE as a valuation metric yields judgments about stocks that are superior to those based upon just PE or normalized PE. To test this proposition, I looked at the correlation between the value sof different metrics, including trailing PE, CAPE, the inverse of the dividend yield, earnings yield and the ratio of Shiller PE to the Bond PE) today and stock returns in the following year and the following five years:
There is both good news and bad news for those who use the Shiller CAPE as their stock valuation metric. The good news is that the fundamental proposition that stocks are more likely to go down in future periods, if the Shiller CAPE is high today, seems to be backed up. The bad news is two fold. First, the relationship is noisy or in investment parlance, the predictive power is low, especially with one-year returns. Second, the trailing PE actually does a better job of predicting one-year returns than the CAPE and while CAPE becomes the better predictor than trailing PE over a five-year period, it is barely better than using a dividend yield indicator.  While I have not included these in the table, I will wager that any multiple (such as EV to EBITDA) would do as good (or as bad, depending on your perspective) a job as market timing.

As a follow-up, I ran a simple test of the payoff to market timing, using the Shiller CAPE and actual stock returns from 1927 to 2016. At the start of every year, I first computed the median value of the Shiller CAPE over the previous fifty years and assumed an over priced threshold at 25% above the median (which you can change). If the actual CAPE was higher than the threshold, I assumed that you put all your money in treasury bills for the following year and that if the CAPE was lower than the threshold, that you invested all your money in equities. (You can alter these values as well). I computed how much $100 invested in the market in 1927 would have been worth in August of 2016, with and without the market timing based on the CAPE:

Download spreadsheet and change parameters
Note that as you trust CAPE more and more (using lower thresholds and adjusting your equity allocation more), you do more and more damage to the end-value of your portfolio. The bottom line is that it is tough to get a payoff from market timing, even when the pricing metric that you are using comes with impeccable credentials. 

3. Investing is relative, not absolute
Notwithstanding its weak spots, let’s take the CAPE as your measure of stock market valuation. Is a CAPE of 27.27 too high, especially when the historic norm is closer to 16? The answer to you may sound obvious, but before you do answer, you have to consider where you would put your money instead. If you choose not to buy stocks, your immediate option is to put your money in bonds and the base rate that drives the bond market is the yield on a riskless (or close to riskless) investment. Using the US treasury bond as a proxy for this riskless rate in the United States, I construct a bond PE ratio using that rate:
Bond PE = 1/ Treasury Bond Rate
Thus, if you invest in a treasury bond on August 22, with a yield of 1.54%, you are effectively making 64.94 (1/.0154) times your earnings. In the graph below, I graph Shiller’s measures of the CAPE against this T.Bond PE from 1960 to 2016:
Download T Bond Rate PE data
I also compute a ratio of stock PE to T.Bond PE that will use as a measure of relative stock market pricing, with a low value indicating that stocks are cheap (relative to T.Bonds) and a high value suggesting the opposite. As you can see, bringing in the low treasury bond rates of the last decade into the analysis dramatically shifts the story line from stocks being over valued to stocks being under valued. The ratio is as 0.42 right now, well below the historical average over any of the time periods listed, and nowhere near the 1.91 that you saw in 2000, just before the dot com bust or  even the 1.04 just before the 2008 crisis. 

4. Its cash flow, not earnings that drives stocks
The old adage that it is cash flows, not earnings, that drives stocks is clearly being ignored when you look at any variant of PE ratios. To provide a sense of what stock prices look like, relative to cash flows, I computed a multiple of total cash returned to stockholders by companies (including buybacks) and compared these multiples to Shiller’s CAPE in the graph below:
S&P 500 Earnings and Cash Payout
Here again, there seems to be a disconnect. While the CAPE has risen for the market, from 20.52 in 2009 to 27.27 in 2016, as stocks soared during that period, the Price to CF ratio has remained stable over that period (at about 20), reflecting the rise in cash returned by US companies, primarily in buybacks over the period.

Am I making the case that stocks are under valued? If I did, I would be just as guilty as those who use CAPE to make the opposite case. I am not a market timer, by nature, and any single pricing metric, no matter how well reasoned it may be, is too weak to capture the complexity of the market. Absolutism in market timing is a sign of either hubris or ignorance.

The Market’s Kryptonite
At this point, if you think that I am sanguine about stocks, you would be wrong, since the essence of investing in equities is that worry goes with it. If it’s not the high CAPE that is worrying me, what is? Here are my biggest concerns, the kryptonite that could drain the market of its strength and vitality.
  1. The Treasury Alternative (or how much are you afraid of your central bank?)  If the reason that you are in stocks is because the payoff for being in bonds is low, that equation could change if the bond payoff improves. If you are Fed-watcher, convinced that central banks are all-powerful arbiters of interest rates, your nightmares almost always will be related to a meeting of the Federal Open Market Committee (FOMC), and in those nightmares, the Fed will raise rates from 1.50% to 4% on a whim, destroying your entire basis for investing in stocks. As I have noted in these earlier posts, where I have characterized the Fed as the Wizard of Oz and argued that low rates are more a reflection of low inflation and anemic growth than the result of quantitative easing, I believe that any substantial rate rises will have to come from shifts in fundamentals, either an increase in inflation or a surge in real growth. Both of these fundamentals will play out in earnings as well, pushing up earnings growth and making the stock market effect ambiguous. In fact, I can see a scenario where strong economic growth pushes T. bond rates up to 3% or higher and stock markets actually increase as rates go up.
  2. The Earnings Hangover It is true that we saw a long stint of earnings improvement after the 2008 crisis and that the stronger dollar and a weaker global economy are starting to crimp earnings levels and growth. Earnings on the S&P 500 dropped in 2015 by 11.08% and are on a pathway to decline again this year and if the rate of decline accelerates, this could put stocks at risk. That said, you could make the case that the earnings decline has been surprisingly muted, given multiple crises, and that there is no reason to fear a fall off the cliff. No matter what your views, though, this will be more likely to be a slow-motion correction, offering chances for investors to get off the stock market ride, if they so desire.
  3. Cash flow Sustainability: My biggest concern, which I voiced at the start of the year, and continue to worry about is the sustainability of cash flows. Put bluntly, US companies cannot keep returning cash at the rate at which they are today and the table below provides the reason why:

YearEarningsDividendsDividends + BuybacksDividend PayoutCash Payout
200138.8515.7430.0840.52%77.43%
200246.0416.0829.8334.93%64.78%
200354.6917.8831.5832.69%57.74%
200467.6819.40740.6028.67%59.99%
200576.4522.3861.1729.27%80.01%
200687.7225.0573.1628.56%83.40%
200782.5427.7395.3633.60%115.53%
200849.5128.0567.5256.66%136.37%
200956.8622.3137.4339.24%65.82%
201083.7723.1255.5327.60%66.28%
201196.4426.0271.2826.98%73.91%
201296.8230.4475.9031.44%78.39%
2013107.336.2888.1333.81%82.13%
2014113.0139.44101.9834.90%90.24%
2015100.4843.16106.1042.95%105.59%
2016 (LTM)98.6143.88110.6244.50%112.18%
In 2015, companies in the S&P 500 collectively returned 105.59% of their earnings as cash flows. While this would not be surprising in a recession year, where earnings are depressed, it is strikingly high in a good earnings year. Through the first two quarters of 2016, companies have continued the torrid pace of buybacks, with the percent of cash returned rising to 112.18%. The debate about whether these buybacks make sense or not will have to be reserved for another post, but what is not debatable is this. Unless earnings show a dramatic growth (and there is no reason to believe that they will), companies will start revving down (or be forced to) their buyback engines and that will put the market under pressure. (For those of you who track my implied equity risk premium estimates, it was this concern about cash flow sustainability that led me to add the option of allowing cash flow payouts to adjust to sustainable levels in the long term).

So, how do these worries play out in my portfolio? They don’t explicitly but they do implicitly affect my investment choices. I cannot do much about interest rates, other than react, and I will stay ready, especially if inflation pressures push up rates and the fixed income market offers me a better payoff. With earnings and cash flows, there may be concerns at the market level, but I bet on individual companies, not markets. With those companies, I can do my due diligence to make sure that they have the operating cash flows (not just dividends or buybacks) to justify their valuations. If that sounds like a pitch for intrinsic valuation, are you surprised?

The Market Timing Mirage
Will there be a market correction? Of course! When it does happen, don't be surprised to see a wave of “I told you so” coming from the bubblers. A clock that is stuck at 12 a'clock will be right twice every day and I would urge you to judge these market timers, not on their correction calls, which will look prescient, but on their overall record. Many of them, after all, have been suggesting that you stay out of stocks for the last five years or longer and it would have to be a large correction for you to make back what you lost from staying on the sidelines. Some of these pundits will be crowned as great market timers by the financial press and they will acquire followers. I hope that I don’t sound like a Cassandra but this much I know, from studying past history. Most of these great market timers usually get it right once, let that success get to their heads and proceed to let their hubris drive them to more and more extreme predictions in the next cycle. As an investor, my suggestion is that you save your money and your sanity by staying far away from market prognosticators.

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Datasets
  1. PE ratios from 1960-2016
  2. Shiller CAPE and T.Bond PE (1960-2016)
  3. S&P 500: Earnings, Dividends and Buybacks (2000-2016)
  4. CAPE Market Timing Test

Mean Reversion: Gravitational Super Force or Dangerous Delusion?

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In my last post on the danger of using  single market metric to time markets, I made the case that though the Shiller CAPE was high, relative to history, it was not a sufficient condition to conclude that US equities were over valued. In the comments that followed, many disagreed. While some took issue with measurement questions, noting that I should have looked at 10-year correlations, not five and one-year numbers, others argued that this metric was never meant for market timing and that the real message was that the expected returns on stocks over the next decade are likely to be low. I was surprised at how few brought what I think is the central question, which is the assumption that the CAPE or any other market metric will move back to historic norm. This unstated belief that things revert back to the way they used to be is both deeply set and at the heart of much of value investing, especially of the contrarian stripe. Thus, when you buy low PE stocks and or sell a stock because it has a high PE, you are implicitly assuming that the PE ratios for both will converge on an industry or market average. I am just as prone to this practice as anyone else, when I do intrinsic valuation, when I assume that operating margins and costs of capital for companies tend to converge on industry norms. That said, I continue to worry about how many of my valuation mistakes occur because I don’t question my assumption about mean reversion enough. So, you should view this post as an attempt to be honest with myself, though I will use CAPE data as an illustrative example of both the allure and the dangers of assuming mean reversion.

Mean Reversion: Basis and Push Back
The notion of mean reversion is widely help and deeply adhered to not just in many disciplines but in every day life. In sports, whether it be baseball, basketball, football or soccer, we use mean reversion to explain why hot (and cold) streaks end. In investments, it is an even stronger force explaining why funds and investors that fly high come back to earth and why strategies that deliver above-average returns are  unable to sustain that momentum.

In statistics, mean reversion is the term used to describe the phenomenon that if you get an extreme value (relative to the average) in a draw of a variable, the second draw from the same distribution is likely to be closer to the average. It was a British statistician, Francis Galton, who first made official note of this process when studying the height of children, he noted that extreme characteristics on the part of parent (a really tall or short parent) were not passed on. Instead, he found that the heights reverted back to what he called a mediocre point, a value-laden word that he used to describe the average. In the process, he laid the foundations for linear regressions in statistics.

In markets and in investing, mean reversion has not only taken on a much bigger role but has arguably had a greater impact than in any other discipline. Thus, Jeremy Siegel's argument for why "stocks win in the long term" is based upon his observation that over a very long time period (more than 200 years), stocks have earned higher returns than other asset classes and that there is no 20-year time period in his history where stocks have not outperformed the competition. Before we embark on on examination of the big questions in mean reversion, let's start by laying out two different versions of mean reversion that co-exist in markets.
  • In time series mean reversion, you assume that the value of a variable reverts back to a historical average. This, in a sense, is what you are using when looking at the CAPE today at 27.27 (in August 2016) and argue that stocks are over priced because the average CAPE between 1871 and 2016 is closer to 16.
  • In cross sectional mean reversion, you assume that the value of a variable reverts back to a cross sectional average. This is the basis for concluding that an oil stock with a  PE ratio of 30 is over priced, because the average PE across oil stocks is closer to 15. 
At the risk of over generalization, much of market timing is built on time series mean reversion, whereas the bulk of stock selection is on the basis of cross sectional mean reversion. While both may draw their inspiration from the same intuition, they do make different underlying assumptions and may pose different dangers for investors.

The nature of markets, though, is that every point of view has a counter, and it should come as no surprise that just as there are a plethora of strategies built around mean reversion, there are almost as many built on the presumption that it will not happen, at least during a specified time horizon. Many momentum-based strategies, such as buying stocks with high relative strength (that have gone up the most over a recent time period) or have had the highest earnings growth in the last few years, are effectively strategies that are betting against mean reversion in the near term. While it is easy to be an absolutist on this issue, the irony is that not only can both sides be right, even though their beliefs seem fundamentally opposed, but worse, both sides can be and often are wrong.

Mean Reversion: The Questions
You can critique mean reversion at two levels. At the level at which it is usually done, it is more about measurement than about process, with arguments centered around both how to compute the mean and the timing and form of the reversion process. There is a fundamental and perhaps more significant critique of the very basis of mean reversion, which is based on structural changes in the process being analyzed.

The Measurement Critique
Let’s say that both you and I both believe in mean reversion. Will we respond to data in the same way and behave the same way? I don't think so and that is because there are layers of judgments that lie under the words “mean” and “reversion”, where we can disagree. 
  • On the mean, the numbers that we arrive at can be different, depending upon the time period you look at (if it time series mean reversion) or the cross sectional sample (if it is a cross sectional mean reversion), and you can get very different values with the arithmetic average as opposed to the median. With cross sectional data, for instance, the oil company analysis may be altered depending on whether your sample is of all oil companies, just larger integrated oil companies or smaller, emerging market oil companies. For time series variations, consider the historical time series of CAPE and how different the "mean" looks depending on the time period used and how it was computed.
  • On the reversion part, there can be differences in judgment as well. First, even if we both agree that there is mean reversion, we can disagree on how quickly it will happen. That has profound consequences for investing, because there may be a time horizon threshold at which we may not be to devise an investment strategy to take advantage of the reversion. Second, we can disagree over how the metric in question will adjust. To illustrate, assume that the mean reversion metric is CAPE and that we both agree that  the CAPE of 27 should drop to the historic norm of 16 over the next decade. This can be accomplished by a drop in stock prices (your market crash) or by a surge in earnings (if you can make an argument that earnings are depressed and are due for recovery). The implications for investing can be very different.
In summary, there is a lot more nuance to mean reversion than its strongest proponents let on. One reason that they try to make their case look stronger than it is may be because they are selling others on their investment thesis and hoping that if they can convince enough people to make it self fulfilling. The other, and perhaps more dangerous reason, is to convince themselves that they are right, as a precursor to action. 

The Fundamental Critique
The process of mean reversion is built on the presumption that the underlying distribution (whether it be a time series or cross sectional) is stationary and that while there may be big swings from year to year (or from company to company), the numbers revert back to a norm. That is the elephant in the room, the really big assumption, that drives all mean reversion and it is its weakest link. If there are structural changes that alter the underlying distribution, there is no quicker way to ruin that trusting in mean reversion.

The types of structural changes that can cause distribution to go awry range the spectrum, and the following is a list, albeit not comprehensive, of why these changes in the context of mean reversion over time.
  • The first is aging, with the argument easiest to make with individual companies and more difficult with entire markets. As companies move through the life cycle, you will generally see the numbers for the company reflect that aging, rather moving to historic norms. That is especially true for growth rates, with growth rates decreasing as a company scales up and becomes more mature, but it is also true of both other operating numbers (margins, costs of capital) as well as pricing metrics (price earnings ratios and EV multiples). While markets, composed of portfolios of companies, are less susceptible to aging, you could argue that aging equity markets (the US, Japan and Europe) will exhibit different characteristics than they did when were younger and more vibrant. 
  • The second is technology and industry structure, shaking up both the product market structure and creating challenges for accountants. This is true clearly at the company level, as is the case with retailing, where Amazon's entry and subsequent growth has laid waste to historic norms for this sector, bringing down operating margins and changing reinvestment patterns. It is also true at the market level, where an increasing proportion of the equity market (say, the S&P 500) are service and technology stocks and the accounting for expenses in these sectors (with many capital expenses being treated as operating expenses) creating questions about whether the E in the PE for the S&P 500 is even comparable over time.
  • The third is changes in consumer and investor preferences, with the first affecting the numbers in product markets and the latter in financial markets. For instance, there is an argument to be made that the surge in index funds has altered how stocks are priced today, as opposed to two or three decades ago.
In the context of CAPE, again, and using Shiller's entire database, which goes back to 1871, let's take a quick look at how much both the US economy has grown and changed since 1871 and how those changes have affected the composition of US stocks.

In 1871, coming out of the civil war, the US was more emerging than developed market, with the growth and risk that goes with that characterization. In 1900, the US equity market had become the largest in the world, but 63% of its value came from railroad stocks, reflecting both their importance to the US economy then and their need for equity capital. For most of the next few decades, the US continued on its path as a growth market and economy, though the growth trend was brought to a stop by the great depression.  The Second World War firmly established the US as the center of the global economy and the period between 1945 and 2000 represents the golden age of mean reversion, a period where at least in the US, mean reversion worked like a charm not just across stocks but across time. It is worth noting that many of the now-accepted standard practices in both corporate finance and valuation, from using historical risk premiums for stocks to attaching premiums for expected returns to small-cap stocks to believing that value stocks beat growth stocks (with low PBV or low PE as a proxy for value) came from researchers poring over this abnormally mean-reverting financial history. I trace my awakening to the dangers of mean reversion to the 2008 crisis but I believe that the signs of structural change were around me for at least a decade prior. After all, the shift from a US-centric global economy to one that was more broadly based started occurring in the 1970s and continued, with fits and bounds, in the decades after. Similarly, the US dollar's reign as the global currency was challenged by the introduction of the Euro in 1999 and put under further strain by the growth in emerging market currencies.

So, how did 2008 change my thinking about markets, investing and valuation? First, globalization is here to stay and while it has brought pluses, it has already brought some minuses. As I noted in my post on country risk, no investor or company can afford to stay localized any more, since not only do market crisis in one country quickly become global epidemics, but a company that depends on just its domestic market for operations (revenues and production) is now more the exception than the rule. Second, the fact that financial service firms were at the center of the crisis, has had long term consequences. Not only has it led to a loss of faith in banks as well-regulated entities, run by sensible (and risk averse) people, but it has increased the role of central bankers in economies, with perverse consequences. In their zeal to be saviors of the economy, central bankers (in my view) have contributed to an environment of low economic growth and higher risk premiums. Third, the low economic growth and low inflation has resulted in interest rates lower than they have been historically in most currencies and negative interest rates in some. I know that there are many who believe that I am over reacting and that it only a question of time before we revert back to more normal interest rates, higher economic growth and typical inflation but I am not convinced. 

From Statistical Significance to Investment Return Payoff
The standard approach to showing mean reversion is start with historical data and establish mean reversion with statistics. I will start with that basis, again using CAPE as my illustrative example, but will then build on it to show why, even if you believe in mean reversion and you base it on sound statistics, it is so difficult to convert statistical significance into market-beating returns.

The statistics
If you were looking at a data series, how would you go about showing mean reversion. There are three simple statistical devices that you can draw. The first is graphical, a scatter plot of the data that shows the mean reversion over time. In the context of CAPE, for instance, this is the graph that you saw in my last post:
Historical data on Shiller CAPE
The problem with this plot is that it is weak evidence for investing, since you don't make money from buying or selling PE but from buying and selling stocks. In fact, even in this plot, you can see that the CAPE case that stocks are over priced is weakened because I have used a 25-year median for comparison. A stronger graphical backing for mean reversion would then graph stock returns in subsequent time periods as  a function of the CAPE today, with a higher CAPE (relative to history) translating into lower returns in a future period. 

Looking at this data, at least, the evidence seems strong that a high CAPE today goes with lower stock returns in future periods, with the mean reversion becoming stronger for longer time periods.

The relationship between the market timing metric and returns can be quantified in one of two ways. You could compute the correlation between the metric and returns, with a more negative correlation indicating stronger mean reversion. Updating my CAPE/ returns correlation metric, with 10-year returns added to the mix, you can see again the basis for the market timing argument:

You an build on these correlations and run regressions (linear or otherwise) where you regress returns in future periods against the value of the metric today. The results of those regressions, with CAPE as the market metric, are summarized below:
What does this mean? If you buy into mean reversion and can live with the noise or error in your estimate (captured in the R-squared), these regressions back up the correlation findings, insofar as your CAPE-based predictions get more precise for longer time period returns. In fact, if you are one of those who lives and dies by statistics, using today's CAPE of 27.27 in this regression will yield a predicted annualized return of 4.30% on stocks for the next 10 years:
Expected annualized return in next 10 years = 16.24% - 0.0044 (27.27) = 4.30%
Scary, right? But before you over react, first recognize that this prediction comes with a standard error and range and second, please read on.

The Investment Action
If you have sat through a statistics class, you have probably heard the oft-repeated caution that "correlation is not causation", a good warning if you are a researcher trying to explain a phenomenon but not particularly relevant, if you are an investor. After all, if you can consistently make a lot of money from a strategy, do you really need to know why? The biggest challenge in investing is whether you can convert statistical significance ( a high correlation or a regression with impressive predictive power) into investment strategy. It is at this level that market timing metrics run into trouble, and using CAPE again, here are the two ways in which you can use the results from the data to change the way you invest.

If you are willing to buy into the notion that the structural changes in the economy and markets have not changed the historical mean reversion tendencies in the CAPE, the most benign and defensible use of the data is to reset expectations. In other words, if you are an investor in stocks today, you should expect to make lower returns for the next 10 years than you have historically. This has consequences for how much investors should save for future retirement or how much states should set aside to cover future contractual obligations, with both set asides increasing because your expected returns are lower. 

It is when you decide to use the CAPE findings to do market timing that the tests become more arduous and difficult to meet. To understand what this means, let's go back to the basic asset allocation decision that all investment begins with. Given your risk aversion (a function of both your psychological make-up and the environment you are in) and liquidity needs (a function of your age, wealth and dependents), there is a certain mix of stocks, bonds and cash that is right for you. With market timing, you will alter this mix to reflect your views on desirable (or under priced) markets and undesirable ones. Thus, your natural mix is 60% stocks, 30% bonds and 10% cash, and you believe (using whatever market timing metric you choose) that stocks are over priced, you would lower your allocation to stocks and increase your allocation to either bonds or cash. You could further refine this market timing algorithm for domestic stocks versus foreign stocks or bring in other asset classes such as collectibles and real estate). The test of a market timing strategy therefore requires more structure than the statistical analysis of checking for correlation or regression:
  1. Timing threshold: If you decide that you will time markets using a metric, you have to follow through with specifics. For instance, with CAPE as your market metric, and a high (low) CAPE being used as an indicator of an over valued (under valued) market, you have to indicate the trigger  that will initiate action. In other words, does the CAPE have to be 10% higher, 25% higher or 50% higher than the historic average for you to start moving money out of stocks?
  2. Asset class alternatives: If you decide to move money out of stocks, you have to also specify where the money will go and you have four choices. 
  3. Holding period: You will have to specify how long you plan to stay with the "market timed" allocation mix, with the answers ranging from a pre-specified time horizon (1 year, 2 years or 5 years) to until the market timing metric returns to safe territory. 
  4. Allocation Constraints (if any): The allocation that you have for an asset class can be floored at zero, if you are a long only investor, but can be negative, if you are willing to go short. The cap on what you can allocate to an asset class is 100%, if you cannot or choose not to borrow money, but can be greater than 100%, if you can. 
Put simply, the lower your threshold, the more alternative you have to stocks, the shorter your holder period and the fewer your constraints, the more active you are as a market timer. It is in this context that I tried out different market timing strategies built around CAPE. The table below lists out the returns from a buy and hold strategy with a fixed mix of stocks, bonds and bills (60%, 30% and 10%) and contrasts it with returns over the same period from using a CAPE timing strategy of reducing the equity allocation to 40% if the CAPE is 25% higher than a 50-year median value and increasing the equity allocation to 80% if the CAPE is 25% lower than a 50-year median value. I report the numbers for the entire time period 1917-2016 and break it down into two fifty-year time periods (1917-1966, 1967-2016)>
Download market timing spreadsheet
With this mix of timing choices (50-year median, 25% threshold and the given changes to equity allocation), the Shiller CAPE outperforms the buy and hold strategy for the 1917-2016 time period  but  under performs in the last fifty year time period. I know that your timing choices can be very different from mine and I have created options in this spreadsheet to let you change the choices to reflect your preferences to see if you can deliver better market timing results using CAPE. I did try a few variants and here is what I found.
  1. Time Period: With every variation of timing that I tried, the CAPE delivers a positive market timing payoff in the first half of the entire time period (from 1917 to 1966) and a negative one in the second half (1967-2016). In fact, I could not find a combination of timing devices that delivered positive payoff in the second time period.
  2. Choice of median: Using the lifetime median delivers better results during the "good" period (1917-1966) but worse results during the "bad" period (1967-2016). Using a shorter time periods for the median reduces the outperformance in the first half of the analysis period but improves it in the second half.
  3. Buy and Sell: The CAPE's timing payoff is greater when it is used as a buying metric than as a selling metric. In fact, you make a positive payoff from using a low CAPE as a buying indicator over the entire period but using it is a signal of over priced markets costs you money in both time period. 
  4. Market Timing magnitude: Increasing the degree to which you tilt towards or away from stocks, in reaction to the CAPE, just magnifies the return difference, positive or negative. Thus, in the first half of the century (1917-1966), changing your equity exposure more increases the payoff to market timing. In the second half, it makes the negative payoff worse.
In many ways, this testing is tilted in favor of finding that the Shiller CAPE works. First, while I have been careful not to use ex-post data, I have acted as if I know what the earnings for the year will be, at the end of each year, when my market timing decision is made. In reality, on December 31, 2012, I would know only the earnings for the first three quarters of 2012 and not quite the full year. Second, I am ignoring the transactions costs and taxes due from shifting large amounts in and out of stocks in my timing years. Those will represent a significant drain on my returns as an investor. Finally, I am assuming that there have been no structural shifts large enough to cause the mean reversion to break down. In spite of all of this, I am hard pressed to explain why we are so swayed by arguments based on this metric.

Conclusion
These are dangerous times for those who believe in mean reversion, for two reasons. The first is that our access to historical data is getting broader and deeper, with mixed consequences. Having more data allows us to extract find out more about the underlying fundamentals but since that data goes back so far, much of what we find may not longer have relevance. The second is that doing statistical analysis no longer requires either homework or effort, with tools at our fingertips and statistical results are only a click away. Both in academia and in practice, I see more and more use of statistical significance as proof that you can beat markets and my reason devising and testing out market timing strategies with CAPE were not meant to be an assault on CAPE but more a cautionary note that statistical correlation is not cash in the bank. This may also explain why there are so many ways to beat the market, on paper, and so few seem to be able to deliver those magical excess returns, in practice. 

YouTube Video

Datasets
  1. CAPE: 1881-2016 (Shiller Data)
  2. Stock, Bond and Bill Returns (1881-2016)
  3. Market Timing Spreadsheet

The School Bell Rings! It's Time for Class!

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As most teachers do, I mark time in academic rather than in calendar years and as September dawns, it is New Year's eve for me and a new class is set to begin. In just under a week, on September 7, 2016, I will walk into a classroom and face up to a roomful of students, not quite ready for summer to end, and start teaching, as I have every year since 1984. This semester, I will be back to teaching Valuation to MBAs at Stern, and as I have in semesters past, I invite you to join me on this journey, as we look at the mix of art, science and magic that makes valuation such a fascinating discipline.

Class Philosophy
I have always believe that to teach a class well, you have to start with a story and that the class is an extended serialization of the story. I also believe that to teach well, you have to, at least over time, make that story your own and mold the class to reflect it. In fact, the valuation class that I will be teaching this Fall has its seeds in the very first valuation class that I taught in 1986, but the differences reflect not only how much the world has changed since then, but also how my own thinking on valuation has evolved. The class remains a work in progress, where each time I teach it, I learn something new as well as recognize how much I have left to learn.

I could give you an extended essay on what this class is about, but I would repeating what I said at the start of the Fall 2015 semester in this post. In short, I said this class is not an extended accounting class (where you forecast entire financial statements for extended periods), or a modeling class (where you become an Excel Ninja) or a theory class (since there is so little of it in  valuation to begin with). Instead, here are the broad themes that underlie this class, all captured in the picture below:

If you find this picture a little daunting, I did do a Google talk that encapsulated these themes into about an hour-long session. 


In particular, this class is less about the tools and techniques of valuation and more about developing a foundation that you can use to build your own investment philosophy. I know that faith is a word that is seldom used and often viewed with suspicion by many in the valuation community, but it is at the heart of this class, both in terms of how you build up faith in your own capacity to value assets and businesses and how you hold on to that faith when the market price moves away from your value.  Since I still struggle on both of these fronts, I cannot give you a template for success but I will be open about my own insecurities both about my own valuations and about markets.

Class Structure
Since my objective in the class is that by the end of it, you should be able to attach a number to just about any asset, I will roam the spectrum. I will start with the basics of intrinsic value, partly because it is where I am most comfortable and partly because it provides me with ways of dealing with other approach. The mechanics of estimating discount rates, cash flows, growth and terminal value are not just simple, but easily mechanized. It is the specifics that we will wrestle with in this class:

  • On risk free rates, usually the least troublesome and more easily obtained input in valuation, we will talk about why risk free rates vary across currencies, what to do about currencies that have negative risk free rates and whether normalizing risk free rates (as many practitioners have taken to doing) is a good idea or a bad one.
  • On risk premiums and discount rates, we will wrestle with questions of what risks should and should not be incorporated into discount rates and the different methods of bringing them in. In the process, we will examine how best to estimate equity risk premiums and default spreads, and why even if you don't like betas or portfolio theory, you should should still be able to estimate discount rates and do intrinsic valuation.  
  • On cash flows, we will focus on why accounting inconsistencies (on dealing with R&D, leases and other items) can lead to misstated earnings and how to fix those inconsistencies, examine what should and should not be included in reinvestment (capital expenditures and working capital) and what to do about stock based compensation.
  • On growth, we will start with the easy cases (where historical earnings growth is a good predictor of future growth) but quickly move on to more difficult cases (of companies in transition) and to what some view as impossible cases (like estimating growth in a start-up)>
  • On terminal value, the big number in every DCF,  that can very quickly hijack otherwise well-done valuations, we will develop simple rules for keeping the number in check and put to sleep many myths surrounding it.
We will apply intrinsic valuation to value companies across the life cycle, in different sectors and across different markets. We will value small and large companies, private and public, developed and emerging and discuss how to value movie franchises (like Star Wars), phenomena (Pokemon Go) and sports teams. We will talk about why start ups can and should be valued in the face of daunting uncertainty and how probabilistic tools (simulations and decision trees) can help.

About half way through the class, we will turn our attention to pricing assets/businesses, where rather than build up to a value from a company's fundamentals, we price it, based on how the market is pricing similar companies. Put simply, we will shine a light on the practice of using pricing multiples (PE, EV/EBITDA, EV/Sales) and comparable companies not with the intent of improving how it is done. We will also talk about why, even when you are careful and take care of the details, your pricing of a company can be very different form its value.

In the last segment of the class, we will stretch our valuation muscles by talking about how option pricing models can sometime be used to estimate the additional value in a business, such as undeveloped reserves for a natural resource company or expansion potential for a young growth firm, and sometimes to value equity in deeply distressed companies. We will close by looking at acquisition valuation, where good sense seems to be in short supply, and how understanding value can be critical to corporate managers.

Want to sit in?
If you are intrigued or interested, you are welcome to sit in on the class (online and unofficially). While my immediate attention will be reserved for the Stern MBAs who will be registered in this class, you will have access to all of the resources that they do, starting with the lectures but also extending to lecture notes, quizzes/exams and even emails. The bad news is that I will be unable to grade your work or give you a certificate of completion. The good news is that the price is right. There are three ways in which you can join the class:

  1. My website: The most comprehensive and most updated center of all things related to this class at this link. You will find the webcasts, lecture notes, past exams, reading and even the emails I send on this class here.
  2. iTunes U: Just as I am not an Excel Ninja, my capacity to deal with html is primitive and my website's design reflects that lack of sophistication. If you prefer more polish, you can try the iTunes U app in the Apple app store. It is a free app that you can download and install on your Apple device. Once you have it installed, click on the add course and enter the enroll code FER-SFJ-AKA. Like magic, the class should pop up on your shelf. If you don't have an Apple device, you can get to the course on your computer using this link. If you have an Android device, you can use a workaround by downloading this app first. Like all things Apple, the set up is amazing and easy to work with.
  3. YouTube: The problem with the first two choices is that they presuppose that you don't have a broadband constraint, perhaps a phone internet connection or worse. My suggestion is that you use the YouTube playlist that I have created for this class at this link. The nice thing about YouTube is that it adjusts the image quality to your connection speed. So, it should work in almost any setting.
Since I have made this offer for almost 20 years now, predating the MOOC boom and bust, I can offer some suggestions. First, it is a lot of work to watch two 80-minute lectures a week, try your hand out at working through actual valuations and finish the class in fifteen weeks, if you have other things going on in your life (and who does not?). My suggestion is that you cut yourself some slack and take more time, since the materials will stay up for at least a year after the class ends. Second, watching a lecture online for almost an hour and a half can be painful and for those of you who find the pain unbearable, I do have an alternative. A couple of years ago, I created an online version of this class, shrinking each 80-minute session into 10-15 minute sessions and this class is also available on my website at this link, on iTunes U at this link and on YouTube. Third, whichever version of the class you take will stick more if you pick a company and value it and even more, if you keep doing it. 

The End Game
I would love to tell you that I live a life of serenity and that I am sharing for noble reasons, but that would not be true. I am sharing my class for the most selfish of all reasons. I am a performer (and every teacher is) and what performer does not wish for a bigger audience? If I am going to prepare and deliver a class, would I not rather have thirty thousand people watch the class than three hundred. If you get something of value from this class, and you feel the urge to repay me, I will make the same suggestion that I did last year. Learning is one of those rare resources that is never diminished by sharing. So, please pass it on to someone else! See you in class!

Links
  1. Entry Page for the Valuation Spring 2016 (on my website)
  2. Webpage for the Valuation Spring 2016 class webcasts (on my website)
  3. iTunes U for the Valuation Spring 2016 class (Enroll code on device: FER-SFJ-AKA)
  4. YouTube Playlist for the Valuation Spring 2016 class
  5. Webpage for Valuation Online class (short sessions)
  6. iTunes U for the Valuation Online class (short sessions)
  7. YouTube for the Valuation Online class (short sessions)

Lazard, Evercore and the TSLA/SCTY Deal: Keystone Kops or Crafty Bankers?

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It is get easy to get outraged by events around you, even when that outrage is not merited. I have learned, through hard experience, that writing when outraged can be cathartic but it can also be dangerous. After all, once you have climbed on your high horse, it is easy to find fault with others and wallow in self-righteousness. It is for that reason that I have deliberately avoided taking issue with specific banking valuations of companies, much as I may disagree with the practices. I understand that bankers make money on transactions and that their valuations are more sales tools than assessments of fair value. Once in a while, though, I do come across a valuation so egregiously bad that I cannot restrain myself and reading through the prospectus filed by Tesla for their Solar City acquisition/merger was such an occasion. My first reaction as I read through the short descriptions of how the bankers in this deal (Evercore for Tesla and Lazard for Solar City) valued the two companies was "You must be kidding me!".

The Tesla/Solar City Deal
In ___, Tesla announced that it intended to acquire Solar City, a surprise to almost everyone involved, except for Elon Musk. The specifics of the deal are still being ironed through but the broad contours of the deal are captured in the picture below:

At the time of the deal, Mr. Musk contended that the deal made sense for stockholders in both companies, arguing that it would ... While Mr. Musk has a history of big claims and perhaps the smarts and charisma to deliver on them, this deal attracted attention because of its optics. Mr. Musk was the lead stockholder in both companies and CEO of Tesla and his cousin, , was the CEO of Solar City. Even Mr. Musk's strongest supporters could not contest the notion that he was in effective control at both companies, creating a potential for conflicts of interests. Those questions have not gone away in the months since and the market concerns have been reflected in the trend lines in the stock prices of the two companies:

The boards of directors at the two companies, and especially at Tesla, have recognized the potential for a legal backlash and as this New York Times article suggests, they have been careful to create at least the appearance of an open process, with Tesla's board hiring Evercore as its deal banker, while Solar City chose Lazard.

The Banking Challenge in a Friendly Merger
In any friendly merger, the bankers on the two sides of the deal face, what at first sight, looks like an impossible challenge. The banker for the acquiring company has to convince the stockholders of the acquiring company that they are getting a good deal, i.e., that they are acquiring the target company at a price, which while higher that the prevailing market price, is lower than the fair value for the company. At the same time, the banker for the target company has to convince the stockholders of the target company that they too are getting a good deal, i.e., that they are being acquired is higher than their fair value. If you are a reasonably clever banking team, you discover very quickly that the only way you can straddle this divide is by bringing in what I call the two magic merger words, synergy and control. Synergy in particular is magical because it allows both sides to declare victory and control adds to the allure because it comes with the promise of unspecified changes that will be made at the target company and a 20% premium:

In the Tesla/Solar City deal, the bankers faced a particularly difficult challenge. Finding synergy in this merger of an electric car company and a solar cell company, one of which (Tesla) has brand name draw and potentially high margins and the other of which is a commodity business (Solar City) with pencil thin margins) is tough to do. Arguing that the companies will be better managed as one company is tricky when both companies have effectively been controlled by the same person(Musk) before the merger. In fact, it is far easier to make the case for reverse synergy here, since adding a debt-laden company with a questionable operation business (Solar City) to one that has promise but will need cash to deliver seems to be asking for trouble.

The bankers could of course have come back and told the management of both companies (or just Elon Musk) that the deal does not make sense and especially so for the stockholders of Tesla but who can blame them for not doing so? After all, they are paid based upon whether the deal gets done and if asked to justify themselves, they would argue that Musk would have found other bankers who would have gone alone. Consequently, I am not surprised that both banks found value in the deal and managed to justify it.

The Valuations
It is with this perspective in mind that I opened up the prospectus, expecting to see two bankers doing what I call Kabuki valuations, elaborately constructed DCFs where the final result is never in doubt, but you play with the numbers to make it look like you were valuing the company. Put differently, I was willing to cut a lot of slack on specifics but I found failed even the minimal tests of adequacy in valuation. Summarizing what the banks did, at least based upon the prospectus (lest I am accused of making up stuff):

Conveniently, they provide backing for the Musk acquisition story, with Evercore reassuring Tesla stockholders that they are getting a good deal and Lazard doing the same with Solar City stockholders, while shamelessly setting a range on value so wide that they have legs cover, in case they get sued. There are many parts of these valuations that I can take issue with, but in the interests of fairness, I will divide up my critique into that of practices that are bad but the defense can be that everyone does it and practices that are indefensible.
1. Use of management forecasts of unaudited numbers:
2. No internal checks for consistency:
3. Discount Rates:
4. Growth Rates and Terminal Value:

Not content with turning one set of questionable valuations, both banks doubled down on what they called a sum of the parts valuation of Solar City.

First, sum of the parts valuation makes sense only if you have separable assets and it i

Keystone Kop Valuations: Lazard, Evercore and the TSLA/SCTY Deal

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It is get easy to get outraged by events around you, but I have learned, through hard experience, that writing when outraged is dangerous. After all, once you have climbed onto your high horse, it is easy to find fault with others and wallow in self-righteousness. It is for that reason that I have deliberately avoided taking issue with investment banking valuations of specific companies, much as I may disagree with the practices used in many of them. I understand that bankers make money on transactions and that their valuations are more sales tools than assessments of fair value and that asking them to pay attention to valuation first principles may be asking too much. Once in a while, though, I do come across a valuation so egregiously bad that I cannot restrain myself and reading through the prospectus filed by Tesla for their Solar City acquisition/merger was such an occasion. My first reaction as I read through the descriptions of how the bankers in this deal (Evercore for Tesla and Lazard for Solar City) valued the two companies was "You must be kidding me!".

The Tesla/Solar City Deal
In June 2016, Tesla announced that it intended to acquire Solar City in a stock swap, a surprise to almost everyone involved, except for Elon Musk. By August 1, the specifics of the deal had been ironed out and the broad contours of the deal are captured in the picture below:


At the time of the deal, Mr. Musk contended that the deal made sense for stockholders in both companies, arguing that it was a "no-brainer" that would allow Tesla to expand its reach and become a clean energy company. While Mr. Musk has a history of big claims and perhaps the smarts and charisma to deliver on them, this deal attracted attention because of its optics. Mr. Musk was the lead stockholder in both companies and CEO of Tesla and his cousin, Lyndon Rive, was the CEO of Solar City. Even Mr. Musk's strongest supporters could not contest the notion that he was in effective control at both companies, creating, at the very least. the potential for conflicts of interests. Those questions have not gone away in the months since and the market concerns have been reflected in the trend lines in the stock prices of the two companies, with Solar City down about 24% and Tesla's stock price dropping about 8%.

The boards of director at at Tesla has recognized the potential for a legal backlash and as this New York Times article suggests, they have been careful to create at least the appearance of an open process, with Tesla's board hiring Evercore Partners, an investment bank, to review the deal and Solar City's board calling in Lazard as their deal assessor. Conspicuously missing is Goldman Sachs, the investment banker on Tesla's recent stock offering, but more about that later.

The Banking Challenge in a Friendly Merger
In any friendly merger, the bankers on the two sides of the deal face, what at first sight, looks like an impossible challenge. The banker for the acquiring company has to convince the stockholders of the acquiring company that they are getting a good deal, i.e., that they are acquiring the target company at a price, which while higher that the prevailing market price, is lower than the fair value for the company. At the same time, the banker for the target company has to convince the stockholders of the target company that they too are getting a good deal, i.e., that they are being acquired is higher than their fair value. If you are a reasonably clever banking team, you discover very quickly that the only way you can straddle this divide is by bringing in what I call the two magic merger words, synergy and control. Synergy in particular is magical because it allows both sides to declare victory and control adds to the allure because it comes with the promise of unspecified changes that will be made at the target company and a 20% premium:


In the Tesla/Solar City deal, the bankers faced a particularly difficult challenge. Finding synergy in this merger of an electric car company and a solar cell company, one of which (Tesla) has brand name draw and potentially high margins and the other of which is a commodity business (Solar City) with pencil thin margins) is tough to do. Arguing that the companies will be better managed as one company is tricky when both companies have effectively been controlled by the same person(Musk) before the merger. In fact, it is far easier to make the case for reverse synergy here, since adding a debt-laden company with a questionable operation business (Solar City) to one that has promise but will need cash to deliver seems to be asking for trouble. The bankers could of course have come back and told the management of both companies (or just Elon Musk) that the deal does not make sense and especially so for the stockholders of Tesla but who can blame them for not doing so? After all, they are paid based upon whether the deal gets done and if asked to justify themselves, they would argue that Musk would have found other bankers who would have gone alone. Consequently, I am not surprised that both banks found value in the deal and managed to justify it.

The Valuations
It is with this perspective in mind that I opened up the prospectus, expecting to see two bankers doing what I call Kabuki valuations, elaborately constructed DCFs where the final result is never in doubt, but you play with the numbers to make it look like you were valuing the company. Put differently, I was willing to cut a lot of slack on specifics but I found failed even the minimal tests of adequacy in valuation. Summarizing what the banks did, at least based upon the prospectus (lest I am accused of making up stuff):
Tesla Prospectus
Conveniently, these number provide backing for the Musk acquisition story, with Evercore reassuring Tesla stockholders that they are getting a good deal and Lazard doing the same with Solar City stockholders, while shamelessly setting value ranges so wide that they get legal cover, in case they get sued.  Note also not only how much money paid to these bankers for their skills at plugging in discount rates into spreadsheets but that both bankers get an additional payoff, if the merger goes through, with Evercore pocketing an extra $5.25 million and Lazard getting 0.4% of the equity value of Solar City.  There are many parts of these valuations that I can take issue with, but in the interests of fairness, I will start with what I term run-of-the-mill banking malpractice, i.e., bad practices that many bankers are guilty of.
  1. No internal checks for consistency: There is almost a cavalier disregard for the connection between growth, risk and reinvestment. Thus, when both banks use ranges of growth for their perpetual value estimates, it looks like neither adjusts the cash flows as growth rates change. (Thus, when Lehman moves its perpetual growth rate for Solar City from 1.5% to 3%, it looks like the cash flow stays unchanged, a version of magical growth that can happen only on a spreadsheet).
  2. Discount Rates: Both companies pay lip service to standard estimation technology (with talk of the CAPM and cost of capital), and I will give both bankers the benefit of the doubt and attribute the differences in their costs of capital to estimation differences, rather than to bias.  The bigger question, though, is why the discount rates don't change as you move through time to 2021, where both Tesla and Solar City are described as slower growth, money making companies.
  3. Pricing and Valuation: I have posted extensively on the difference between pricing an asset/business and valuing it and how mixing the two can yield a incoherent mishmash. Both investment banks move back and forth between intrinsic valuation (in their use of cash flows from 2016-2020) and pricing, with Lehman estimating the terminal value of Tesla using a multiple of EBITDA. (See my post on dysfunctional DCFS, in general, and Trojan Horse DCFs, in particular).
There are two aspects of these valuations that are the over-the-top, even by banking valuation standards:
  1. Outsourcing of cash flows: It looks like both bankers used cash flow forecasts provided to them by the management. In the case of Tesla, the expected cash flows for 2016-2020 were generated by Goldman Sachs Equity Research (GSER, See Page 99 of prospectus) and for Solar City, the cash flows for that same period were provided by Solar City, conveniently under two scenarios, one with a liquidity crunch and one without. Perhaps, Lazard and Evercore need reminders that if the CF in a DCF is supplied to you by someone else,  you are not valuing the company, and charging millions for plugging in discount rates into preset spreadsheets is outlandish. 
  2. Terminal Value Hijinks: The terminal value is, by far, the biggest single number in a DCF and it is also the number where the most mischief is done in valuation. While some evade these mistakes by using pricing, there is only one consistent way to get terminal value in a DCF and that is to assume perpetual growth. While there are a multitude of estimation issues that plague perpetual growth based terminal value, from not adjusting the cost of capital to reflect mature company status to not modifying the reinvestment to reflect stable growth, there is one mistake that is deadly, and that is assuming a growth rate that is higher than that of the economy forever. With that context, consider these clippings from the prospectus on the assumptions about growth forever made by Evercore in their terminal value calculations:
    Tesla Prospectus
    I follow a rule of keeping the growth rate at or below the risk free rate but I am willing to accept the Lehman growth range of 1.5-3% as within the realm of possibility, but my reaction to the Evercore assumption of 6-8% growth forever in the Tesla valuation or even the 3-5% growth forever with the Solar City valuation cannot be repeated in polite company. 
Not content with creating one set of questionable valuations, both banks doubled down with a number of  of other pricing/valuations, including sum-of-the-parts valuations, pricing and transaction premiums, using a "throw everything at the fan and hope something sticks" strategy.

Now what? 
I don't think that Tesla's Solar City acquisition passes neither the smell test (for conflict of interest) nor the common sense test (of creating value), but I am not a shareholder in either Tesla or Solar City and I don't get a vote. When Tesla shareholders vote, given that owning the stock is by itself an admission that they buy into the Musk vision, I would not be surprised if they go along with his recommendations. Tesla shareholders and Elon Musk are a match made in market heaven and I wish them the best of luck in their life together.

As for the bankers involved in this deal, Lazard's primary sin is laziness, accepting an assignment where they are reduced to plugging in discount rates into someone else's cash flow forecasts and getting paid $2 million plus for that service. In fact, that laziness may also explain the $400 million debt double counting error made by Lazard on this valuation,. Evermore's problems go deeper. The Evercore valuation section of the prospectus is a horror story of bad assumptions piled on impossible ones, painting a picture of ignorance and incompetence. Finally, there is a third investment bank (Goldman Sachs), mentioned only in passing (in the cash flow forecasts provided by their equity research team), whose absence on this deal is a story by itself. Goldman's behavior all through this year, relating to Tesla, has been rife with conflicts of interest, highlighted perhaps by the Goldman equity research report touting Tesla as a buy, just before the Tesla stock offering. It is possible that they decided that their involvement on this deal would be the kiss of death for it, but I am curious about (a) whether Goldman had any input into the choice of Evercore and Lazard as deal bankers, (b) whether Goldman had any role in the estimation of Solar City cash flows, with and without liquidity constraints, and (c) how the Goldman Sachs Equity Research forecast became the basis for the Tesla valuations. Suspicious minds want to know! As investors, the good news is that you have a choice of investment bankers but the bad news is that you are choosing between the lazy, the incompetent and the ethically challenged.

If there were any justice in the world, you would like to see retribution against these banks in the form of legal sanctions and loss of business, but I will not hold my breath waiting for that to happen. The courts have tended to give too much respect for precedence and expert witnesses, even when the precedent or expert testimony fails common sense tests and it is possible that these valuations, while abysmal, will pass the legally defensible test. As for loss of business, my experience in valuation is that rather than being punished for doing bad valuations, bankers are rewarded for their deal-making prowess. So, for the many companies that do bad deals and need an investment banking sign-off on that deal (in the form of a fairness opinion), you will have no trouble finding a banker who will accommodate you.

If this post comes across as a diatribe against investment banking, I am sorry and I am not part of the "Blame the Banks for all our problems" school. In fact, I have long argued that bankers are the lubricants of a market economy, working through kinks in the system and filling in capital market needs and defended banking against its most virulent critics. That said, the banking work done on deals like the this one vindicate everyone's worst perceptions of bankers as a hired guns who cannot shoot straight, more Keystone Kops than Wyatt Earps!

YouTube Video


Attachments
  1. Tesla Prospectus for Solar City Deal

Fairness Opinions: Fix them or Get Rid of them!

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My post on the Tesla/SCTY deal about the ineptitude and laziness that Lazard and Evercore brought to the valuation process did not win me any friends in the banking M&A world. Not surprisingly, it drew some pushback, not so much from bankers, but from journalists and lawyers, taking me to task for not understanding the context for these valuations. As Matt Levine notes in his Bloomberg column, where he cites my post, "a fairness opinion is not a real valuation, not a pure effort to estimate the value of a company from first principles and independent research" (Trust me. No one is setting the bar that high. I was looking for biased efforts using flawed principles and haphazard research and these valuation could not even pass that standard)  and that "they (Lazard and Evercore) are just bankers; their expertise is in pitching and sourcing and negotiating and executing deals -- and in plugging in discount rates into preset spreadsheets -- not in knowing the future". (Bingo! So why are they doing these fairness opinions and charging millions of dollars for doing something that they not good at doing? And there is a difference between knowing the future, which no one does, and estimating the future, which is the essence of valuation.) If Matt is right, the problems run deeper than the bankers in this deal, raising questions about what the purpose of a   "fairness opinion" is and whether we it has outlived its usefulness (assuming that it was useful at some point).

Fairness Opinions: The Rationale
What is a fairness opinion? I am not a lawyer and I don't play intend to play one here, but it is perhaps best to revert back to the legal definition of the term. In an excellent article on the topic, Steven Davidoff defines a fairness opinion as an "opinion provided by an outsider that a transaction meets a threshold level of fairness from a financial perspective". Implicit in this definition are the assumptions that the outsider is qualified to pass this judgment and that there is some reasonable standard for fairness.  In corporate control transactions (acquisition, leveraged buyout etc.), as practiced today, the fairness opinion is delivered (orally) to the board at the time of the transaction, and that presentation is usually followed by a written letter that summarizes the transaction term,and the appraiser's assumptions and attests that the price paid is "fair from a financial point of view". That certainly sounds like something we should all favor, especially in deals that have obvious conflicts of interest, such as management-led leveraged buyouts or transactions like the Tesla/Solar City deal, where the interests of Elon Musk and the rest of Tesla 'sstockholders may diverge.

Note that while fairness opinions have become part and parcel of most corporate control transactions, they are not required either by regulation or law. As with so much of business law, especially relating to acquisitions, the basis for fairness opinions and their surge in usage can be traced back to Delaware Court judgments. In Smith vs Van Gorkom, a 1985 case, the court ruled against the board of directors of Trans Union Corporation, who voted for a leveraged buyout, and specifically took them to task for the absence of a fairness opinion from an independent appraiser. In effect, the case carved out a safe harbor for the companies by noting that “the liability could have been avoided had the directors elicited a fairness opinion from anyone in a position to know the firm’s value”.  I am sure that the judges who wrote these words did so with the best of intentions, expecting fairness opinions to become the bulwark against self-dealing in mergers and acquisitions. In the decades since, through a combination of bad banking practices, the nature of the legal process and confusion about the word "fairness", fairness opinions, in my view, have not just lost their power to protect those that they were intended to but have become a shield used by managers and boards of directors against serious questions being raised about deals. 

Fairness Opinions: Current Practice?
There are appraisers who take their mission seriously and evaluate the fairness of transactions in their opinions but the Tesla/Solar City valuations reflect not only how far we have strayed from the original idea of fairness but also how much bankers have lowered the bar on what constitutes acceptable practice.  Consider the process that Lazard and Evercore used by  to arrive at their fairness opinions in the Tesla/Solar City deal, and if Matt is right, they are not alone:

What about this process is fair, if bankers are allowed to concoct discount rates, and how is it an opinion, if the numbers are supplied by management? And who exactly is protected if the end result is a range of values so large that any price that is paid can be justified?  And finally, if the contention is that the bankers were just using professional judgment, in what way is it professional to argue that Tesla will become the global economy (as Evercore is doing in its valuation)? 

To the extent that what you see in the Tesla/Solar City deal is more the rule than the exception, I would argue that fairness opinions are doing more harm than good. By checking off a legally required box, they have become a way in which a board of directors buy immunization against legal consequences. By providing the illusion of oversight and an independent assessment, they are making shareholders too sanguine that their rights are being protected. Worse of all, this is a process where the worst (and least) scrupulous appraisers, over time, will drive out the best (and most principled) ones, because managers (and boards that do their bidding) will shop around until they find someone who will attest to the fairness of their deal, no matter how unfair it is. My interest in the process is therefore as much professional, as it is personal. I believe the valuation practices that we see in many fairness opinions are horrendous and are spilling over into the other valuation practices.

It is true that there are cases, where courts have been willing to challenge the "fairness" of fairness opinions, but they have been infrequent and  reserved for situations where there is an egregious conflict of interest. In an unusual twist, in a recent case involving the management buyout of Dell at $13.75 by Michael Dell and Silver Lake, Delaware Vice Chancellor Travis Lester ruled that the company should have been priced at $17.62, effectively throwing out the fairness opinion backing the deal. While the good news in Chancellor Lester's ruling is that he was willing to take on fairness opinions, the bad news is that he might have picked the wrong case to make his stand and the wrong basis (that markets are short term and under price companies after they have made big investments) for challenging fairness opinions.

Fish or Cut Bait?
Given that the fairness opinion, as practiced now, is more travesty than protection and an expensive one at that, the first option is to remove it from the acquisition valuation process. That will put the onus back on judges to decide whether shareholder interests are being protected in transactions. Given how difficult it is to change established legal practice, I don't think that this will happen. The second is to keep the fairness opinion and give it teeth. This will require two ingredients to work, judges that are willing to put fairness opinions to the test and punishment for this who consistently violate those fairness principles.

A Judicial Check
Many judges have allowed bankers to browbeat them into accepting the unacceptable in valuation, using the argument that what they are doing is standard practice and somehow professional valuation.  As someone who wanders across multiple valuation terrain, I am convinced that the valuation practices in fairness opinions are not just beyond the pale, they are unprofessional. To those judges, who would argue that they don't have the training or the tools to detect bad practices, I will make my pro bono contribution in the form of a questionnaire with flags (ranging from red for danger to green for acceptable) that may help them separate the good valuations from the bad ones.

Question
Green
Red
Who is paying you to do this valuation and how much? Is any of the payment contingent on the deal happening? (FINRA rule 2290 mandates disclosure on these)
Payment reflects reasonable payment for valuation services rendered and none of the payment is contingent on outcome
Payment is disproportionately large, relative to valuation services provided, and/or a large portion of it is contingent on deal occurring.
Where are you getting the cash flows that you are using in this valuation?
Appraiser estimates revenues, operating margins and cash flows, with input from management on investment and growth plans.
Cash flows supplied by management/ board of company.
Are the cash flows internally consistent?
1.     Currency: Cash flows & discount rate are in same currency, with same inflation assumptions.
2.     Claim holders: Cash flows are to equity (firm) and discount rate is cost of equity (capital).
3.     Operations: Reinvestment, growth and risk assumptions matched up.
No internal consistency tests run and/or DCF littered with inconsistencies, in currency and/or assumptions.
-       High growth + Low reinvestment
-       Low growth + High reinvestment
-       High inflation in cash flows + Low inflation in discount rate
What discount rate are you using in your valuation?
A cost of equity (capital) that starts with a sector average and is within the bounds of what is reasonable for the sector and the market.
A cost of equity (capital) that falls outside the normal range for a sector, with no credible explanation for difference.
How are you applying closure in your valuation?
A terminal value that is estimated with a perpetual growth rate < growth rate of the economy and reinvestment & risk to match.
A terminal value based upon a perpetual growth rate > economy or a multiple (of earnings or revenues) that is not consistent with a healthy, mature firm.
What valuation garnishes have you applied?
None.
A large dose of premiums (control, synergy etc.) pushing up value or a mess of discounts (illiquidity, small size etc.) pushing down value.
What does your final judgment in value look like?
A distribution of values, with a base case value and distributional statistics.
A range of values so large that any price can be justified.

If this sounds like too much work, there are four changes that courts can incorporate into the practice of fairness opinions that will make an immediate difference:
  1. Deal makers should not be deal analysts: It should go without saying that a deal making banker cannot be trusted to opine on the fairness of the deal, but the reason that I am saying it is that it does happen. I would go further and argue that deal makers should get entirely out of the fairness opinion business, since the banker who is asked to opine on the fairness of someone else's deal today will have to worry about his or her future deals being opined on by others.
  2. No deal-contingent fees: If bias is the biggest enemy of good valuation, there is no simpler way to introduce bias into fairness opinions than to tie appraisal fees to whether the deal goes through. I cannot think of a single good reason for this practice and lots of bad consequences. It should be banished.
  3. Valuing and Pricing: I think that appraisers should spend more time on pricing and less on valuation, since their focus is on whether the "price is fair" rather than on whether the transaction makes sense. That will require that appraisers be forced to justify their use of multiples (both in terms of the specific multiple used as well as the value for that multiple) and comparable firms. If appraisers decide to go the valuation route, they should take ownership of the cash flows, use reasonable discount rates and not muddy up the waters with arbitrary premiums and discounts. And please, no more terminal values estimated from EBITDA multiples!
  4. Distributions, not ranges: In my experience, using a range of value for a publicly traded stock to determine whether a price is fair is useless. It is analogous to asking, "Is it possible that this price is fair?, a question not worth asking. Instead, the question that should be asked and answered is "Is it plausible that this price is a fair one?"  To answer this question, the appraiser has to replace the range of values with a distribution, where rather than treat all possible prices as equally likely, the appraiser specifies a probability distribution. To illustrate, I valued Apple in May 2016 and derived a distribution of its values:

Let's assume that I had been asked to opine on whether a $160 stock price is a fair one for Apple. If I had presented this valuation as a range for Apple's value from $80.81 to $415.63, my answer would have to be yes, since it falls within the range. With a distribution, though, you can see that a $160 price falls at the 92nd percentile, possible, but neither plausible, nor probable.  To those who argue that this is too complex and requires more work, I would assume that this is at the minimum what you should be delivering, if you are being paid millions of dollars for an appraisal.

Punishment
The most disquieting aspect of the acquisition business is the absence of consequences for bad behavior, for any of the parties involved, as I noted in the aftermath of the disastrous HP/Autonomy merger. Thus, managers who overpay for a target are allowed to use the excuse of "we could not have seen that coming" and the deal makers who aided and abetted them in the process certainly don't return the advisory fees, for even the most abysmal advice. I think while mistakes are certainly part of business, bias and tilting the scales of fairness are not and there have to be consequences:
  1. For the appraisers: If the fairness opinion is to have any heft, the courts should reject fairness opinions that don't meet the fairness test and remove the bankers involved  from the transaction, forcing them to return all fees paid. I would go further and create a Hall of Shame for those who are repeat offenders, with perhaps even a public listing of their most extreme offenses. 
  2. For directors and managers: The boards of directors and the top management of the firms involved should also face sanctions, with any resulting fines or fees coming out of the pockets of directors and managers, rather than the shareholders involved.
I know that your reaction to these punitive suggestions is that they will have a chilling effect on deal making. Good! I believe that much as strategists, managers and bankers like to tell us otherwise, there are more bad deals than good ones and that shareholders in companies collectively will only gain from crimping the process.

YouTube Video


Attachments
  1. The Fairness Questionnaire (as a word file, which you are free to add to or adapt)

Venture Capital: It is a pricing, not a value, game!

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Venture capitalists (VCs) don’t value companies, they price them! Before you explode, implode or respond with righteous indignation, this is not a critique of what venture capitalists do, but a recognition of reality. In fact, not only is pricing exactly what you should expect from VCs but it lies at the heart of what separates the elite from the average venture capitalist. I was reminded of this when I read a response from Scott Kupor of Andreessen Horowitz, to a Wall Street Journal article about Andreessen, that suggested that the returns earned by the firm on its funds were not as good as those earned at other elite funds. While Scott’s intent was to show that the Wall Street Journal reporter erred in trusting total returns as a measure of VC performance, I think that he, perhaps unintentionally, opened a Pandora’s box when he talked about how VCs attach numbers to companies and how these numbers get updated, and how we (investors, founders and VCs) should read them, as a consequence.

The WSJ versus the VC: A Recap
Let’s start with the Wall Street Journal article that triggered the Kupor response. With the provocative title of “Andreessen Horowitz’s returns trail venture capital elite”, it had all the ingredients for click bait, since a big name (Andreessen Horowitz) failing (“trail venture capital elite”) is always going to attract attention. I must confess that I fell for the bait and read the article and walked away unimpressed. In effect, Rolfe Winkler, the Journal reporter, took the three VC funds run by Andreessen and computed an IRR based upon the realized and unrealized gains at these funds. I have reproduced his graph below:

While the title of the story is technically correct, I am not sure that there is much of a story here. Even if you take the Journal’s estimates of returns at face value, if I were an investor in any of the three Andreessen funds, I would not be complaining about annual returns of 25%-42%, depending on the fund that I invested in. Arguing that I could have done better by investing in a fund in the top 5% of the VC universe would be the equivalent of claiming that Kevin Durant did not having a good NBA season last year, because Lebron James and Stephan Curry had better seasons.

In the hyper-competitive business of venture capital, though, the article must have drawn blood, since it drew Scott Kupor's attention and a response. Scott focused attention specifically on what he believed was the weakest link in the Journal article, the combining of realized and unrealized gains to estimate an internal rate of return. Unlike investments in public equities, where the unrealized returns are based upon observed market prices for traded stocks and can be converted to realized returns relatively painlessly, Scott noted that unrealized returns at venture capital funds are based upon estimates and that these estimates are themselves based upon opaque VC investments in other companies in the space and not easily monetized. Implicitly, he seemed to be saying that not only are unrealized returns at VC funds subject to estimation error, but also to bias, and should thus be viewed as softer than realized returns. I agree, though I think it is disingenuous to go on to argue that unrealized returns should not be considered when evaluating venture capital performance, since VCs seem to have qualms about using them in sales pitches when they serve their purpose.

The VC Game
The Kupor response has been picked in the VC space, with some commenters augmenting legitimate points about return measurement but many more using the WSJ article to restate their view that non-VC people should stop opining about the VC business, because they don’t understand how it works. Having been on the receiving end of this critique at times in the past, you would think I would know better than to butt in, but I just can’t help myself. I may not be qualified to talk about the inner workings of the venture capital business, but I do believe that I am on firmer ground on the specific topic of how VCs attach numbers to the companies that they invest in.

VCs price businesses, not value them!
I have made the distinction between value and price so many times before that I sound like a broken record, but I will make it again. You can value an asset, based upon its fundamentals (cash flows, growth and risk) or price it, based upon what others are paying for similar assets, and the two can yield different numbers.

In public investing, I have argued that this plays out in whether you choose to play the value game (invest in assets where the price < value and hope that the market corrects) or the pricing game (where you trade assets, buying at a lower price and hoping to sell at a higher).  I would be glad to be offered evidence to the contrary but based upon the many VC "valuations" that I have seen, VCs almost always play the pricing game, when attaching numbers to companies, and there are four ways in which they seem to do it:
  1. Recent pricing of the same company: In the most limited version of this game, a prospective investor in a private business looks at what investors in prior rounds have priced the company to gauge whether they are getting a reasonable price. Thus, for an Uber, this would imply that a pricing close to the $62.5 billion that the Saudi Sovereign fund priced the company at, when it invested $3.5 billion in June 2016, will become your benchmark for a reasonable price, if you are investing close to that date. The dangers in doing this are numerous and include not only the possibility of a pricing mistake spiraling up or down but also the problems with extrapolating to the value of a company from a VC investment in it.
  2. Pricing of “similar” private companies: In a slightly more expanded version of this process, you would look at what investors are paying for similar companies in the “same space” (with all of the subjective judgments of what comprises “similar” and “same space”), scale this price to revenues, or lacking that, a common metric for that space, and price your company. Staying in the ride sharing space, you could price Lyft, based upon the most recent Uber transaction, by scaling the pricing of the company to its revenues (relative to Uber) or to rides or number of cities served.
  3. Pricing of public companies, with post-value adjustments: In the rare cases where a private business has enough operating substance today, in the form of revenues or even earnings, in a space where there are public companies, you could use the pricing of public companies as your basis for pricing private businesses. Thus, if your private business is in the gaming business and has $100 million in revenues and publicly traded companies in that business trade at 2.5 times revenues, your estimated value would be $250 million. That value, though, assumes that you are liquid (as publicly companies tend to be) and held by investors who can spread their risks (across portfolios). Consequently, a discount for lack of liquidity and perhaps diversification is applied, though the magnitude (20%, 30% or more) is one of the tougher numbers to estimate and justify in practice.
  4. Forward pricing: The problem with young start-ups is that operating metrics (even raw ones like riders, users or downloads) are often either non-existent or too small to be base a pricing. To get numbers of any substance, you often have to forecast out the metrics two, three or five years out and then apply a pricing multiple to these numbers. The forecasted metric can be earnings, or if that still is ephermal, it can be revenues, and the pricing multiple can be obtained not just from private transactions but from the public market (by looking at companies that have gone public). That forward value has to be brought back to today and to do so, venture capitalists use a target rate of return. While this target rate of return plays the same mechanical role that a discount rate in a DCF does, that is where the resemblance ends. Unlike a discount rate, a number designed to incorporate the risk in the expected cash flows for a going concern, a target rate of return incorporates not just conventional going-concern risk but also survival risk (since many young companies don’t make it) and the fear of dilution (a logical consequence of the cash burn at young companies) and becomes a negotiating tool. Even the occasional VC intrinsic value (taking the form of a DCF) is a forward pricing in disguise, with the terminal value being estimated using a multiple on that year's earnings or revenues.

    At the time of a VC investment, the VC wants to push today’s pricing for the company lower, so that he or she can get a greater share of the equity for a given investment in the company. Subsequent to the investment, the VC will want the pricing to go higher for two reasons. First, it makes the unrealized returns on the VC portfolio a much more attractive number. Second, it also means that any subsequent equity capital raised will dilute the VC’s ownership stake less. If you reading this as a criticism of how venture capitalists attach numbers to companies, you are misreading it because I think that this is exactly what venture capitalists should be doing, given how success is measured in the business. This is a business where you are measured less on the quality of the companies that you build (in terms of the cash flows and profits they generate) and more on the price you paid to get into the business and the price at which you exit this business, with that exit coming from either an IPO or a sale. Consequently, how much you are willing to pay for something becomes a process of judging what you will get when you exit and working backwards.
But Venture Capitalists have a data problem
It is not just venture capitalists who play the pricing game. As I have argued before, most investors in public markets (including many who call themselves value investors) are also in the pricing game, though they use pricing metrics of longer standing (from PE to EV/EBITDA) and have larger samples of public traded firms as comparable firms. The challenges with adapting this pricing game to venture capital investments are primarily statistical:
  1. Small Samples: If your pricing is based upon other private company investments, your sample sizes will tend to be much smaller, if you are a VC than if you a public company investor. Thus, as an investor in a publicly traded oil company, I can draw on 351 publicly traded firms in the US or even the 1029 publicly traded companies globally, when making relative value or pricing judgments. A VC investor pricing a ride sharing company is drawing on a sample of less than ten ride sharing firms globally.
  2. With Infrequent Updating: The small sample problem is exacerbated by the fact that unlike public companies, where trading is frequent and prices get updated for most of the companies in my sample almost continuously, private company transactions are few and far between. In many ways, the VC pricing problem is closer to the real estate pricing than conventional stock pricing, where you have to price a property based upon similar properties that have sold in the recent past.
  3. And Opaque transactions: There is a third problem that makes VC pricing complicated. Unlike public equities, where a share of stock is (for the most part) like any other share of stock and the total market value is the share price times number of shares outstanding, extrapolating from a VC investment for a share in a company to the overall value of equity can be and often is complicated. Why? As I noted in an earlier post on unicorn valuations, the VC investment at each stage of capital-raising is structured differently, with a myriad of options embedded in it, some designed for protection (against dilution and future equity rounds) and some for opportunity (allowing future investments at favorable prices). As I noted in that post, a start-up with a "true" value of $750 million can structure an investment, where the VC pays $50 million (instead of $37.5 million) for 5% of the company, by adding enough optionality to the investment. I may be misreading Scott's section on using option pricing to price VC investments, but if I am reading it right, I think Scott is saying that Andreessen uses option pricing models to clean up for the add-on options in VC investments to get to the fair value. Put differently, Andreessen would put a value of $750 million on this company rather than the $1 billion that you would get from extrapolating from the $50 million for 5%.
I am sure that nothing that I have said here is new to venture capitalists, founders and those close to the VC process, but it is the subtle differences that throw off those whose primary experience is in the public markets. That is one reason that public investors should take the numbers that are often bandied about as valuations of private companies (like Palantir, Uber and Airbnb) with a grain of salt.  It is also why I think that public investors like mutual funds and university endowment funds should either tread lightly or not all in the space. Even within the VC business, it is sometimes easy, especially in buoyant times to forget how much the entire pricing edifice rests as much on momentum and mood, as it does on the underlying fundamentals.

With Predictable Consequences
So, let’s see. VCs price companies and that pricing is often based upon really small samples with infrequently updated and tough-to-read data. The consequences are predictable.
  1. The pricing estimates will have more noise (error) attached to them. The pricing that I obtain for Lyft, based upon the pricing of Uber, Didi Chuxing and GrabTaxi, will have a larger band around the estimate and there is a greater chance that I will eb wrong. 
  2. The pricing will be more subjective, since you have the freedom to choose your comparable firms and often can use discretion to adjust for the infrequent data updating and the complexity of equity investments. While that may seem to just be a restatement of the first critique, there is also a much greater potential for bias to enter into the process. Not surprisingly, therefore, not all VC returns are created equal, especially when it comes to the unrealized portion, with more aggressive VCs reporting “higher” returns than less aggressive VCs. That is perhaps the point being made by Scott about realized versus unrealized returns.
  3. The pricing will lag the market: It is a well-established fact that the capital coming into the VC business ebbs and flows across time, with the number of transactions increasing in up market and dropping in down markets. When there is a severe correction (think 2000 or 2009), transactions can come to a standstill, making repricing difficult, if not impossible. If VCs hold off on full repricing until transactions pick up again, there can be a significant lag between when prices drop at young companies and those price drops getting reflected in returns at VC firms.
  4. There is a price feedback loop: Since VC pricing is based upon small samples with infrequent transactions, it is susceptible to feedback loops, where one badly priced transaction (in either direction) can trigger many more badly priced transactions. 
  5. And a time horizon issue: The lack of liquidity and small samples that get in the way of pricing holdings also introduce a constraint into the pricing game. Unlike public market investors, where the pricing game can be played in minutes or even fractions of a minute on liquid stocks, private market pricing requires patience and more of it, the younger a company is. Put differently, winning at the VC pricing game may require that you take a position in a young start up and bide your time until you build it up and find someone who will find it attractive enough to offer you a much higher price for it. This is perhaps what Scott was talking about, in his response, when he talked about this being VC investing being a "long" game.
There is one final point that also needs to be made. Much as we like to talk about the VC market and the public market as separate, populated by different species, they are linked at the hip. To the extent that a venture capitalist has to plot an exit, either in an initial public offering or by selling to a publicity traded company, if the public market catches a cold, the venture capital market will get pneumonia.
    The VC Edge
    If I were to summarize the entire post in a couple of sentences, here is what it would say. Venture capitalists price the companies they invest in, base that pricing on small samples of opaque transactions and the pricing is therefore more likely to be wrong and lag reality. That sounds pretty damning, but I think that it works to their advantage. That may sound contradictory, but here is my basis for making that statement.
    1. On average: Both VC and public market investors play the pricing game, with the latter having the advantage of more and better data, but over time, venture capitalists seem to deliver better results than public market investors, as seen in the graph below. These are raw returns and I do realize that you have to adjust for risk, but some of the biggest risks in venture capital (failure risk) have already been incorporated into long term returns. 
      Source: Cambridge Associates
    2. The Elite: The most successful VCs not only earn higher returns than the top decile of public market investors but that there seems to be more consistency in the VC business, insofar as the best of the VCs are able to generate higher returns across longer time periods. That would suggest that they bring more durable competitive advantages to the investing game than public market investors.
    How do I reconcile my argument that the VC pricing game is inherently more error-prone and noisy with the fact that VCs seem to make money at it? I think that the very factors that make it so difficult to price and profit of a VC investment are what allow VCs collectively to earn excess returns and the very best VCs to set themselves apart from the rest. In particular, the best in the business set themselves apart from the rest on three dimensions:
    1. They are better pricers (relatively): As Scott notes in his piece, the price that you can attach to a VC investment can vary widely across investors and he uses the example of how Andreessen's option pricing approach can yield a lower pricing for the same company than an alternative approach. While all of these prices are undoubtedly wrong (because they are estimates), some of them are less wrong than others. Repeating a statement that I have made before, you don't have to be right to make money, you just have to be less wrong than everyone else and the chances of you doing that are greater in the VC pricing game.
    2. They can influence the pricing game: Unlike public market investors, who for the most part can observe company metrics but not change them, venture capitalists can take a more active role in the companies that they invest in, from informally advising managers to more formal roles as board members, helping them to decide what metrics to focus on, how to improve these metrics and to cash in on them (from an IPO or a sale).
    3. They have better timing: The pricing game is all about timing, and the VC pricing game is more emphatically so. To be successful, you not only have to time your entry into a business right but even more critically, time your exit from it. 
    If you are an investor in a VC fund, therefore, you should of course look at both realized returns and unrealized returns, but you should also look at how the fund measures its unrealized returns and how it has generated its returns. A realized return that comes primarily from one big hit is clearly less indicative of skill than a return that reflects multiple hits over longer time periods. After all, if separating luck from skill is difficult in the public marketplace, it can become even more so in the venture capital business.

    Deutsche Bank: A Greek Tragedy at a German Institution?

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    This may be a stereotype, but the Germans are a precise people and while that precision often gets in the way of more creative pursuits (like cooking and valuation), it lends itself well to engineering and banking. For decades until the introduction of the Euro and the creation of the European Central Bank, there was no central bank in the world that matched the Bundesbank for solidity and reliability. Thus, investors and regulators around the world, I am sure, are looking at the travails of Deutsche Bank in the last few weeksand wondering how the world got turned upside down. I am sure that there are quite a few institutions in Greece, Spain, Portugal and Italy who are secretly enjoying watching a German entity be at the center of a market crisis. Talk about schadenfreude!

    Deutsche Bank's Journey to Banking Hell
    There are others who have told the story about how Deutsche Bank got into the troubles it is in, much more creatively and more fully than I will be able to do so. Consequently, I will stick with the numbers and start by tracing Deutsche Bank’s net income over the last 28 years, in conjunction with the return on equity generated each year.

    If Deutsche Bank was reluctant to follow more daring competitors into risky businesses for much of the last century, it threw caution to the winds in the early part of the last decade, as it grew its investment banking and trading businesses and was rewarded handsomely with higher earnings from 2000 to 2007. Like almost every other bank on earth, the crisis in 2008 had a devastating impact on earnings at Deutsche, but the bank seemed to be on a recovery path in 2009, before it relapsed. Some of its recent problems reflect Deutsche’s well chronicled pain in investment banking, some come from its exposure to the EU problem zone (Greece, Spain, Portugal) and some from slow growth in the European economy. Whatever the reasons, in 2014 and 2015, Deutsche reported cumulative losses of close to $16 billion, leading to a management change, with a promise that things would turn around under new management. The other dimension where this crisis unfolded was in Deutsche’s regulatory capital, and as that number dropped in 2015, Deutsche Bank's troubles moved front and center. This is best seen in the graph below of regulatory capital (Tier 1 Capital) from 1998 to 2015, with the ratio of the Tier 1 capital to risk adjusted assets each year super imposed on the graph. 


    The ratio of regulatory capital to risk adjusted assets at the end of 2015 was 14.65%, lower than it was in 2014, but much higher than capital ratios in the pre-2008 time-period. That said, with the tightening of regulatory capital constraints after the crisis, Deutsche was already viewed as being under-capitalized in late 2015, relative to other large banks early this year. The tipping point for the current crisis came from the decision by the US Department of Justice to levy a $14 billion fine on Deutsche Bank for transgressions related to the pricing of mortgage backed securities a decade ago. As rumors swirled in the last few weeks, Deutsche Bank found itself in the midst of a storm, since the perception that a bank is in trouble often precipitates more trouble, as rumors replace facts and regulators panic. The market has, not surprisingly, reacted to these stories by marking up the default risk in the bank and marking down the stock price, most strikingly over the last two weeks, but also over a much longer period. 

    At close of trading on October 4, 2016, the stock was trading at $13.33 as share, yielding a market capitalization of $17.99 billion, down more than 80% from its pre-2008 levels and 50% from 2012 levels. Reflecting more immediate fears of default, the Deutsche CDS and CoCo bonds also have dropped in price, and not surprisingly, hedge funds sensing weakness have moved in to short the stock. 

    Revaluing Deutsche Bank
    When a stock is down more than 50% over a year, as Deutsche is, it is often irresistible to many contrarian investors, but knee jerk contrarian investing, i.e., investing in a stock just because it has dropped a lot, is a dangerous strategy. While it is true that Deutsche Banks has lost a large portion of its market capitalization in the last five years, it is also true that the fundamentals for the company have deteriorated, with lower earnings and hits to regulatory capital. To make an assessment of whether Deutsche is now “cheap”, you have to revalue the company with these new realities built in, to see if the market has over reacted, under reacted or reacted correctly to the news. (I will do the entire valuation in US dollars, simply for convenience, and it is straightforward to redo the entire analysis in Euros, if that is your preferred currency).

    a. Profitability 
    As you can see from the graph of Deutsche’s profits and return on equity, the last twelve months have delivered blow after blow to the company, but that drop has been a long time coming. The bank has had trouble finding a pathway to make sustainable profits, as it is torn between the desire of some at the bank to return to its commercial banking roots and the push by others to explore the more profitable aspects of trading and investment banking. The questions in valuation are not only about whether profits will bounce back but also what they will bounce back to. To make this judgment, I computed the returns on equity of all publicly traded banks globally and the distribution is below: 
    Global Bank Data
    I will assume that given the headwinds that Deutsche faces, it will not be able to improve its returns on equity to the industry median or even its own cost of equity in the near term. I will target a return on equity of 5.85%, at the 25th percentile of all banks, as Deutsche’s return on equity in year 5, and assume that the bank will be able to claw back to earning its cost of equity of 9.44% (see risk section below) in year 10. The estimated return on equity, with my estimates of common equity each year (see section of regulatory capital) deliver the following projected net income numbers. 
    YearCommon EquityROEExpected Net Income
    Base$64,609 -13.70%$(8,851)
    1$71,161 -7.18%$(5,111)
    2$72,754 -2.84%$(2,065)
    3$74,372 0.06%$43
    4$76,017 1.99%$1,512
    5$77,688 5.85%$4,545
    6$79,386 6.57%$5,214
    7$81,111 7.29%$5,910
    8$82,864 8.00%$6,632
    9$84,644 8.72%$7,383
    10$86,453 9.44%$8,161
    Terminal Year$87,326 9.44%$8,244
    I am assuming that the path back to profitability will be rocky, with losses expected for the next two years, before the company is able to turn its operations around. Note also that these expected losses are in addition to the $10 billion fine that I have estimated for the DOJ.

    b. Regulatory Capital 
    Deutsche Bank’s has seen a drop in it Tier 1 capital ratios over time but it now faces the possibility of being further reduced as Deutsche Bank will have to draw on it to pay the US DOJ government fine. While the DOJ has asserted a fine of $14 billion, Deutsche will negotiate to reduce it to a lower number and it is assessing its expected payment to be closer to $6 billion. I have assumed a total capital drop of $ 10 billion, leaving me with and adjusted regulatory capital of $55.28 billion and a Tier 1 capital ratio of 12.41%. Over the next few years, the bank will come under pressure from both regulators and investors to increase its capitalization, but to what level? To make that judgment, I look at Tier 1 capital ratios across all publicly traded banks globally: 
    Global Bank Data
    I will assume that Deutsche Bank will try to increase its regulatory capital ratio to the average (13.74%) by next year and then push on towards the 75th percentile value of 15.67%. As the capital ratio grows, the firm will have to increase regulatory capital over the next few years and that can be seen in the table below: 

    YearNet IncomeRisk-Adjusted AssetsTier 1 Capital/ Risk Adjusted AssetsTier 1 CapitalChange in Tier 1 CapitalFCFE = Net Income - Change in Tier 1
    Base$(8,851)$445,570 12.41%$55,282
    1$(5,111)$450,026 13.74%$61,834 $6,552 $(11,663)
    2$(2,065)$454,526 13.95%$63,427 $1,593 $(3,658)
    3$43 $459,071 14.17%$65,045 $1,619 $(1,576)
    4$1,512 $463,662 14.38%$66,690 $1,645 $(133)
    5$4,545 $468,299 14.60%$68,361 $1,671 $2,874
    6$5,214 $472,982 14.81%$70,059 $1,698 $3,516
    7$5,910 $477,711 15.03%$71,784 $1,725 $4,185
    8$6,632 $482,488 15.24%$73,537 $1,753 $4,880
    9$7,383 $487,313 15.46%$75,317 $1,780 $5,602
    10$8,161 $492,186 15.67%$77,126 $1,809 $6,352
    Terminal Year$8,244 $497,108 15.67%$77,897 $771 $7,472
    The negative free cash flows to equity in the first three years will have to be covered with new capital that meets the Tier 1 capital criteria. By incorporating these negative free cash flows to equity in my valuation, I am in effect reducing my value per share today for future dilution, a point that I made in a different context when talking about cash burn

    c. Risk
    Rather than follow the well-trodden path of using risk free rates, betas and risk premiums, I am going to adopt a short cut that you can think of as a model-agnostic way of computing the cost of equity for a sector. To illustrate the process, consider the median bank in October 2016, trading at a price to book ratio of 1.06 and generating a return on equity of 9.91%. Since the median bank is likely to be mature, I will use a stable growth model to derive its price to book ratio: 
    Plugging in the median bank’s numbers into this equation and using a nominal growth rate set equal to the risk free rate of 1.60% (in US dollars), I estimate a US $ cost of equity for the median bank to be 9.44% in 2016. 

    Using the same approach, I arrive at estimates of 7.76% for the banks that are at the 25th percentile of risk and 10.20% for banks at the 75th percentile.  In valuing Deutsche Bank, I will start the valuation by assuming that the bank is at the 75th percentile of all banks in terms of risk and give it a cost of equity of 10.20%. As the bank finds its legs on profitability and improves its regulatory capital levels, I will assume that the cost of equity moves to the median of 9.44%. 

    The Valuation 
    Starting with net income from part a, adjusting for reinvestment in the form of regulatory capital in part b and adjusting for risk in part c, we obtain the following table of numbers for Deutsche Bank. 

    YearFCFETerminal ValueCost of equity Cumulative Cost of EquityPV
    1$(11,663)10.20%1.1020$(10,583.40)
    2$(3,658)10.20%1.2144$(3,012.36)
    3$(1,576)10.20%1.3383$(1,177.54)
    4$(133)10.20%1.4748$(90.34)
    5$2,874 10.20%1.6252$1,768.16
    6$3,516 10.05%1.7885$1,965.99
    7$4,185 9.90%1.9655$2,129.10
    8$4,880 9.74%2.1570$2,262.34
    9$5,602 9.59%2.3639$2,369.91
    10$6,352 $87,317 9.44%2.5871$36,206.88
    Total value of equity $31,838.74
    Value per share =$22.97
    Note that the big number as the terminal value in year 10 reflects the expectation that Deutsche will grow at the inflation rate (1% in US dollar terms) in perpetuity while earning its cost of equity. Note also that since the cost of equity is expected to change over time, the cumulated cost of equity has to be computed as the discount factor. The discounted present value of the cash flows is $31.84 billion, which when divided by the number of shares (1,386 million) yields a value of $22.97 per share. There is one final adjustment that I will make and it reflects the special peril that banks face, when in crisis mode. There is the possibility that the perception that the bank is in trouble could make it impossible to function normally and that the government will have to step in to bail it out (since the option of letting it default is not on the table). I may be over optimistic but I attach only a 10% chance to this occurring and assume that my equity will be completely wiped out, if it occurs. My adjusted value is: 
    Expected Value per share = $22.97(.9) + $0.00 (.1) = $20.67 
    Given my many assumptions, the value per share that I get for Deutsche Bank is $20.67. To illustrate how much the regulatory capital shortfall (and the resulting equity issues/dilution) and overhang of a catastrophic loss affect this value, I have deconstructed the value per share into its constituent effects: 
    Unadjusted Equity Value =$33.63
    - Dilution Effect from new equity issues$(10.66)
    - Expected cost of equity wipeout$(2.30)
    Value of equity per share today =$20.67

    Note that the dilution effect, captured by taking the present value of the negative FCFE in the first four years, reduces the value of equity by 31.69% and the possibility of a catastrophic loss of equity lowers the value another 6.83%.

    I know that you will disagree with some or perhaps all of my assumptions. To accommodate those differences, I have set up my valuation spreadsheet to allow for you to replace my assumptions with yours. If you are so inclined, please do enter your numbers into the shared Google spreadsheet that I have created for this purpose and let's get a crowd valuation going!

    Time for action or Excuse for inaction? 
    At the current stock price of $13.33 (at close of trading on October 4), the stock looks undervalued by about 36%, given my estimated value, and I did but the stock at the start of trading yesterday. Like everyone else in the market, I am uncertain, but waiting for the uncertainty to resolve itself is not a winning strategy. Either the uncertainty will be resolved (in good or bad ways) and everyone will have clarity on what Deutsche is worth, and the price and value will adjust, or the uncertainty will not resolve itself in the near future and you will be sitting on the side lines. For those of you who have been reading my blog over time, you know that I have played this game before, with mixed results. My bets on JP Morgan (after its massive trading loss in 2012) and Volkswagen (after the emissions scandal) paid off well but my investment in Valeant (after its multiple scandals) has lost me 15% so far (but I am still holding and hoping). I am hoping that my Deutsche Bank investment does better, but I strapped in for a rocky ride!

    YouTube Videos


    Attachments

    1. My valuation of Deutsche Bank
    2. Global Banks - Data
    3. Google Shared Spreadsheet: Crowd Valuation of Deutsche Bank

    Myth 4.1: If you don't like betas (or modern portfolio theory),you cannot do a DCF!

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    Let’s start by stating the obvious. You need a D(iscount rate) to do D(iscounted) C(ash) F(low) valuation. To get that discount rate, I use a beta to estimate a cost of equity (and cost of capital) in my valuation and it is that input that evokes the biggest backlash from people perusing the valuation. Many investors have a visceral mistrust of anything that emerges from portfolio theory and betas to them symbolize what they see as the academic view of valuation. Consequently, not only do they take issue with the discount rates that I use in my valuations, they often choose not to do discounted cash flow valuation, because of their discount rate disagreements. Talk about throwing the baby out with the bathwater!

    The D in the DCF: Big Picture Perspective

    To understand the role that the discount rate plays in discounted cash flow valuation, it is worth going back to the DCF equation for the value of an asset with a life of n years, with expected cashflows (E(CF)) in each time period in the numerator and the discount rate (r) in the denominator.
    Note that in a conventional DCF, the numerator has expected cash flows (across all scenarios, good and bad) and it is the denominator (the discount rate) that carries the burden of adjusting for risk. In the context of valuing a business, this risk-adjusted number can take two forms, depending on how the valuation is structured.

    You can stay equity-focused, estimate cash flows to equity (dividends or potential dividends) and discount back at a risk-adjusted rate of return demanded by equity investors (the cost of equity) or you can value the entire business, discounting cash flows to both equity investors and lenders (a pre-debt cash flow) at a weighted average of the cost of equity and the cost of debt, with the latter adjusted for tax benefits on borrowing. If you take the latter path, the discount rate, in addition to carrying the weight of reflecting the risk in your operations now also carries an added burden of incorporating the value added or destroyed by your financing choices (captured in your costs of debt, equity and capital). Note that a DCF model is agnostic about the process that you use to estimate the discount rate and does not require any specific model (with our without betas).

    Estimating Discount Rates – The Portfolio Theory Construct
    The question that you face in valuation then becomes how best to estimate the discount rates (costs of equity & capital), given the fact that they are not easily observable. The advent of portfolio theory in the 1950s and the subsequent development of the capital asset pricing model in the next decade have been both a boon and a bane for discounted cash flow valuation.

    The groundbreaking insight that Harry Markowitz brought to this process was his recognition that the risk in an investment can look very different to one who has all of his or her money in that investment than from one who has his or her money spread across multiple investments. Looking at risk through the eyes of a diversified marginal investor not only changes our definition of risk (to risk that cannot be diversified away) but allows us to measure it with a beta (in the CAPM) and with betas (in multi-factor and arbitrage pricing models), offering pathways to estimating costs of equity for companies.
    Risk and Return Models: Modern Portfolio Theory
    ModelAssumptionsRisk Measure
    The CAPM(1) There are no transactions costs.
    (2) There is no private information.
    The marginal investors will be fully diversified and hold a portfolio of every traded asset in the market. The risk of an individual asset will be captured by the risk added to this market portfolio, and estimated  with a single beta, measured against the market.
    The APMThe market prices of stocks are the best indicators of market and firm-specific risks, with market risks affecting all or many stocks and firm-specific risks not.Historical stock returns can be analyzed to identify the market risk factors and the exposure of each stock to those factors. Since this is a statistical model, the factors will be unnamed. The risk in a stock will be captured with betas, measured against these unnamed factors.
    The Multifactor ModelMarket risk factors have to be macroeconomic, to affect many stocks at the same time. Looking at how a stock behaves, relative to different macroeconomic variables, should yield clues to its market risk exposure.The risk in a stock will be captured with betas, measured against specified macroeconomic factors.
    Easier access to stock price data has allowed us to estimate the beta or betas for individual companies, leading us inexorably to where we are today, where cost of capital calculations have become mechanical processes, with inputs being outsourced to services.

    If you don’t like betas…
    There are many analysts who disagree with the marginal investor assumption and the resulting focus on just non-diversifiable risk. There are perhaps just as many old-time value investors who believe that it is inconsistent to use a price-based risk measure in intrinsic valuation. I see merit in their points of view, but I don't believe that their prescription of abandoning discounted cash flow valuation all together is appropriate. If you are a non-believer in either portfolio theory or in price-based risk measures, there are alternative ways of estimating discount rates that may be more in line with your views on markets, as long as you identify the basis for your disagreement, i.e., whether it is with the assumption that the marginal investor is diversified or with the use of price-based risk measures. The figure below lists the alternatives:
    Alternative Models for Risk Measurement
    Thus, if your quibble is with the diversified marginal investor assumption, you can use a relative risk measure based upon the total risk in an investment (and not just the non-diversifiable risk), a proxy model for discount rates (where you relate them market capitalization, price to book or price momentum) or even a market-determined implied return (backed out of current prices). If you have issues with price-based risk measures, you should consider using variability in accounting earnings, measures of default risk or even qualitative measures (risk classes or sector-based risk measures) to come up with discount rates.

    The bottom line
    In my view, portfolio theory has advanced the cause of estimating discount rates by introducing three common sense components into valuation. The first is that the risk in an investment is the risk that it adds to a portfolio and not based upon it standing alone. The second is that as small investors, we are price takers, with prices set by the larger investors (usually institutional and mostly diversified). The third is that there is information in the stock price movements, with volatility in stock prices reflecting higher underlying risk, than in alternative measures of business performance (like earnings or cash flows). I will continue to use betas in estimating costs of equity, while recognizing their limitations and being willing to adapt to specific circumstances (like valuing private businesses or closely held companies, where the underlying assumptions are most likely to be violated). If you disagree with my point of view, you are on solid ground, as long as you recognize that you will now have to come up with an alternate risk measure that you can live with. If that risk measure is based upon accounting numbers (earnings, debt ratio) or on company characteristics (size, sector), you should recognize that it comes with its own set of problems and be willing to correct for them. Paraphrasing Milton Friedman, it takes a model to beat a model!

    YouTube Video


    Attachments
    1. Cost of Capital: The Swiss Army Knife of Finance (An Overview Paper on Cost of Capital)
    DCF Myth Posts
    Introductory Post: DCF Valuations: Academic Exercise, Sales Pitch or Investor Tool
    1. If you have a D(discount rate) and a CF (cash flow), you have a DCF.  
    2. A DCF is an exercise in modeling & number crunching. 
    3. You cannot do a DCF when there is too much uncertainty.
    4. It's all about D in the DCF ( Myths 4.1, 4.2, 4.3, 4.4 & 4.5)
    5. If most of your value in a DCF comes from the terminal value, there is something wrong with your DCF.
    6. A DCF requires too many assumptions and can be manipulated to yield any value you want.
    7. A DCF cannot value brand name or other intangibles. 
    8. A DCF yields a conservative estimate of value. 
    9. If your DCF value changes significantly over time, there is something wrong with your valuation.
    10. A DCF is an academic exercise.

      Myth 4.2: It's all about D in the DCF

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      If you have taken a class on valuation, think back to what you spent most of your time doing and I will wager you spent it talking about discount rates. If there was any attention paid to cash flows and growth, it was either cursory or mechanical, and perhaps as a set up to returning to the discount rate discussion. I blame both practitioners and academia for this focus. The practitioner obsession with discount rates can be seen both in the time spent talking about discount rates at conferences and on estimating it in valuation. Reviewing the academic literature over the last few decades, the preponderance of it has been focused on developing models to estimate expected returns on risky investments (discount rates). As a result, classical portfolio theory and discounted cash flow valuation have become so entangled that, as I noted in my last post, there are those who on losing faith with portfolio theory have also felt the need to abandon DCF valuation as well.

      The Discount Rate Obsession
      Why are we so focused on discount rates in valuation? One reason is that we attribute more consequence to getting it wrong than we should, partly because of the very first valuation models that we are exposed to. The other is that spending time on the inputs into discount rates gives us a false sense of both control and precision. 

      The roots of discounted cash flow valuation, at least as practiced today, can be traced back almost 80 years to a treatise by John Williams on value, but its popular usage was tied to the development the Gordon Growth Model, where it was simplified for use with dividends in constant growth. 
      Note that this simplified equation is built on two assumptions: that companies pay out what they can afford to (excess cash) in dividends and that these dividends can grow at a constant rate forever. In this model, it is easy to see why the valuation exercise becomes one of estimating discount rates since the dividends are known and the growth rate is constrained to be less than equal to the economy. In fact, staying with the constant growth model, which is how the terminal value is estimated in more expansive versions of the DCF (with free cash flows replacing dividends and high growth periods as front ends to the terminal value), the effect of changing the discount rate on value can be considerable. To illustrate this, I estimate the value per share for a company that is expected to pay a dividend per share of $1.00 next year, growing 3% a year in perpetuity, for costs if equity (discount rates) ranging from 4% to 10%.
      No wonder estimating discount rates paralyzes analysts, since getting it wrong could lead you to value a $16.67 stock (if 10% is the right discount rate) at $100 (if you use 4% as the discount rate).

      There is also a behavioral component at play in the discount rate focus. When faced with significant uncertainty in valuation, it is comforting to turn our attention back to discount rates, where we can draw on established models and data to estimate and fine tune the components (risk premiums, betas, costs of debt). Estimating risk free rates, betas and equity risk premiums to the second, third or even fourth decimal points offers the illusion of control in a world where estimates of revenue growth and operating margins are difficult.

      The Cross Sectional Distribution of Cost of Capital
      Is the focus on discount rates merited? How important is it to get the discount rate right? To answer that question, it is best to look at the numbers. At the start of 2016, as I have at the start of each of the prior years, I estimated the costs of capital for individual companies in a process that I described more fully in this post. The graph below provides the distribution of costs of capital, in US dollars, for US companies at the start of 2016:

      The most striking feature of this graph is the bunching together of costs of capital around 8.5%, with half of all companies having costs of capital between 6.6% and 9.20%. Expanding the sample to look at all 41,889 companies listed globally, you do get a wider distribution, even in US dollar terms, as you get bigger differences in country risk play out in the computation.

      Even in this broader sample, the costs of capital, in US $, of most global companies lies in a tight range, with 50% of companies falling between 7.43% and 10.15%. Moving to other currencies will cause the costs of capital to change, not because there is currency risk, but because of differences in inflation. Thus, the range for cost of capital, in Indian rupee terms, allowing for an inflation differential of 5% with the US dollar, would mean that the range in rupee terms will be 12.43% to 15.15% for half of all global companies.

      Conclusion
      Instead of spending most of our time during valuation estimating discount rates and debating how best to measure risk, as we are prone to do, we will be better served spending more time estimating expected cash flows and growth rates, since big mistakes in valuation are more likely to be made there. While I would make this statement about any company, it is particularly true for younger companies and in the face of uncertainty about the future. In fact, let me propose a compromise. If you have to value a US company in a hurry, why not just use a cost of capital of 8% in July 2016, the median value for US stocks, and spend your limited time on the numerator (cash flows)?
        YouTube Video


        Attachments

        1. Costs of Equity & Capital by Industry Group: US
        2. Costs of Equity & Capital by Industry Group: Global

        DCF Myth Posts
        Introductory Post: DCF Valuations: Academic Exercise, Sales Pitch or Investor Tool
        1. If you have a D(discount rate) and a CF (cash flow), you have a DCF.  
        2. A DCF is an exercise in modeling & number crunching. 
        3. You cannot do a DCF when there is too much uncertainty.
        4. It's all about D in the DCF
        5. If most of your value in a DCF comes from the terminal value, there is something wrong with your DCF.
        6. A DCF requires too many assumptions and can be manipulated to yield any value you want.
        7. A DCF cannot value brand name or other intangibles. 
        8. A DCF yields a conservative estimate of value. 
        9. If your DCF value changes significantly over time, there is something wrong with your valuation.
        10. A DCF is an academic exercise.

          Myth 4.3: The D cannot change (over time) in a DCF

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          In my last post, I argued that academics and practitioners pay too much attention to discount rates in valuation and too little to cash flows. One reason for that attention may by the fear that you have only one shot at estimating the cost of equity or capital, when valuing a firm, and that once estimated, that number becomes the discount rate to use on cash flows in perpetuity. In this post, I will argue that this fear is misplaced and that the DCF approach not only allows for changing discount rates over time but requires it for most firms. 

          The Mechanics of Time-varying Discount Rates 
          In a discounted cash flow valuation, the value of an asset is the present value of the expected cash flows, with the equation written as follows: 
          Written in this form, the “r” in the denominator is the discount rate and is estimated as the cost of equity (or capital), depending on the cash flows that are being discounted. In practice, analysts seem to operate under the presumption that they get one shot at estimating these discount rates, at the start of the process, and that these discount rates are then fixed in perpetuity.  That presumption is wrong, since the DCF structure flexible enough to allow for time varying discount rates, with the modified version of the value equation below: 
          Note that r1 is the discount rate for year 1, r2 is the discount rate in year 2 and so on until your get to your terminal value and the discount rate in perpetuity is rN. There is one minor computational detail which can have major valuation effects. Note that, in the presence of time varying discount rates, the way we do discounting changes. Rather than discount back each year’s cash flow at that year’s discount rate, we compute a compounded discount rate in earn period. Thus, if your cost of capital is 12% in year 1, 11% in year 2 and 10% in year 3, the present value of $100 million in year 3 is as follows:


          If this cash flow had been discounted back (by mistake) at 10% for 3 years, the present value would have been (wrongly) computed to be $75.13 million. Intuitively, you are adjusting the present value of cash flows later for the risk that you have to live through in the earlier years. 

          The Intuition for Time-varying Discount Rate 
          Adjusting discount rates across time may seem like a needless complication but it is a necessary one, if you want your valuation to remain internally consistent. More specifically, if you are assuming changes in your company characteristics (growth, business mix, geographical exposure) in your cash flows, as you move through time, you should be changing the discount rate to reflect these changes. 

          While this is true for all companies, the effect will be greater when you are valuing young companies or companies in transition, where you expect large changes in the company as you move through your forecast period. Thus, in my valuations of Uber in 2014 (a young growth company) and Tesla in July 2016 (a growth company in transition) & Apple in 2016 (a mature company with solid cash flows), my discount rates changed over time.
          How much do these changing discount rates affect the values per share? Considerably, as can be seen in the graph below where I contrast the values that I would have obtained for the three companies with my default assumption of changing discount rates with the values that I would have obtained if the discount rates had been left at the starting levels.
          Value with time-varying Discount RateValue with constant discount RateEffect on value
          Uber (June 2014)$5,895 $3,601 -38.91%
          Tesla (July 2016)$22,364 $17,688 -20.91%
          Apple (May 2016)$692,852 $633,336 -8.59%

          With Uber, the effect on value is substantial, increasing the value of equity by almost ___ but with Apple, the effect is more muted.

          Guidelines for Discount Rate Adjustments
          If you buy into the argument that the costs of equity and capital can change over time, it may seem like that your estimation problems have multiplied, since you now have to not only estimate the current cost of capital for a firm but costs of capital every year through your valuation. To simplify the estimation process, here is what I find works for me: 
          1. To estimate the cost of capital that you will use in the early years (years 1 and 2), start with the current cost of capital for the firm. That will reflect the existing business mix for the firm (in the beta), the geography of its revenues (in the equity risk premium) and the debt policy for the firm (in the cost of debt and debt ratio). 
          2. If the company has clearly specified plans to change its debt ratio and business mix in the near term, adjust the cost of capital for these changes in the near years (years 3-5) for these changes. If it does not, leave the cost of capital at the current level.
          3. The cost of capital in steady state (for terminal value) should move towards those of mature firms. If you see your firm growing across multiple businesses, that cost of capital should be that of the market (with a beta of one, a debt ratio close to the market average) but if you see it growing within only its existing business, the cost of capital should be reflecting of the industry average (reflecting the industry average beta and debt ratio). 
          4. In the transition period (between the near years and steady state), you should adjust the cost of capital from your near-year level to stable growth levels, using linear increments. 
          PhaseForecast yearsBeta Equity Risk PremiumDebt RatioCost of debt
          Start of valuationYr 1-2Reflects current business mixCurrent geography of operationsCurrent market debt ratioCurrent bond rating or default risk assessment
          Build upYrs 3-5Changes in business mix (if any)Changes in geography (if any)Targeted debt ratio (if any)Default risk, given new debt ratio
          TransitionYrs 6-10Move incrementally to stable period betaAdjust to stable period ERPAdjust to stable period debt ratioAdjust to stable period cost of debt
          Stable growth (Steady State)Year 10 & beyondMove to 1, if company grows across businesses, or to industry average, if it stays within businessSteady state geographic exposure and equity risk premium estimates for long term.Market-average debt ratio (if growth across businesses) or industry-average debt ratio (if single business)Stable company cost of debt
          One reason that I compute the costs of capital, by industry grouping, and update it each year is to have access to this information whenever I value a company. If you are interested, you can find the industry average costs of equity and capital for US firms and global firms on my website. 

          If you open the door to adjusting discount rates for changes in company characteristics, you can also consider also bringing in changes in the macroeconomic inputs. In particular, you could allow the risk free rate and risk premiums (in the form of default spreads and equity risk premiums) to change over time, and as they do, so will your discount rate. Thus, if you believe, as many do, that risk free rates are “too low” (given fundamentals) but are wary of replacing actual rates with your estimates, you could have your cake and eat it too, by starting off with current risk free rates and adjusting those rates to what you believe are more normal levels over time. If you do so, though, you should also normalize equity risk premiums and default spreads over time. To provide an illustration, consider the cost of equity for an average-risk (beta =1_ company in US dollars in October 2016, with the US dollar risk free rate at 1.6% and the mature market equity risk premium at about 6%. 
          Cost of equity = Risk free rate + Beta (ERP) = 1.6% + 1 (6%) = 7.6% 
          Let’s assume that you believe that the risk free rate should be closer to 3%, given inflation and real growth today, and that you believe that the market rate will move towards this number over the next decade. Let’s also assume that you also believe that as risk free rates normalize, the equity risk premium will move back towards its average over the last decade (about 5%) The cost of equity for your company ten years from now (which you will use in your terminal value calculation) will then be 8%: 
          Cost of equity in year 10 = Expected Risk free rate + Beta (ERP) = 3% + 1 (5%) = 8% 
          If you are a company with substantial emerging market exposure (say in India or Brazil), you may also be adjusting the additional country risk premium that you incorporate into your cost of equity over time. 

          Conclusion 
          One reason that analysts often feel helpless, when computing intrinsic value in a DCF, is because they feel that they not only have little control over the discount rate, since all the inputs come from outside, but that they are stuck with this discount rate forever. If your discount rates adjust over time to reflect changes in your company, towards industry or market averages, these rates will start to have a smaller effect on your valuations and that is not only healthy but more realistic (at least in my view).

          YouTube Video


          Attachments
          1. Costs of equity & capital by industry: US companies
          2. Costs of equity & capital by industry: Global companies
          DCF Myth Posts
          Introductory Post: DCF Valuations: Academic Exercise, Sales Pitch or Investor Tool
          1. If you have a D(discount rate) and a CF (cash flow), you have a DCF.  
          2. A DCF is an exercise in modeling & number crunching. 
          3. You cannot do a DCF when there is too much uncertainty.
          4. It's all about D in the DCF ( Myths 4.1, 4.2, 4.3, 4.4 & 4.5)
          5. If most of your value in a DCF comes from the terminal value, there is something wrong with your DCF.
          6. A DCF requires too many assumptions and can be manipulated to yield any value you want.
          7. A DCF cannot value brand name or other intangibles. 
          8. A DCF yields a conservative estimate of value. 
          9. If your DCF value changes significantly over time, there is something wrong with your valuation.
          10. A DCF is an academic exercise.

          Myth 4.4: The D(discount) rate is a receptacle for your hopes and fears

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          In discounted cash flow valuation, discount rates are the instruments that we use to adjust for the risk in cash flows. In practice, discount rates often take on a far greater role. Some analysts use dthem to bring in the quality of management, pushing down discount rates for what they perceive as well-managed firms and pushing up discount rates for poor management. Venture capitalists pump up discount rates to compensate themselves for failure risk, i.e., that many of the firms that they invest in will not make it. While these adjustments may seem intuitive, they are dangerous for many reasons: you can double count both the good and bad, you may be adjusting for risks you should not be and biasing your valuations. 

          Management Quality, Competitive Advantages and Discount Rates 
          It remains almost an act of faith in some old-time value investing circles that the rate of return that you should demand on an investment (or discount rate) should reflect the quality of its management and competitive advantages (or moats). Though this seems intuitive, it is not true for a simple reason. Management quality and moats will affect the expected earnings and cash flows, with better quality management and bigger moats delivering higher earnings and cash flows (than for firms without these qualities) but the relationship with risk and discount rates remain tenuous, at best.  That is because risk has to do with uncertainty about levels, rather than levels.

          To see why, consider two companies with vastly different management in the same business. Company A, with “high quality” managers in place is aggressive in its pursuit of growth while also being discriminating, a rare combination that delivers an expected operating margin of 8%, with high variability, with values ranging from 5% to 11%. Company B has a management team whose governing style is inertia, delivering sub-par margins of 3% but with much less variability (2.5% - 3.5%). In this example, company A will have a higher cost of capital than company B but with its higher cash flows, it will also be worth a great deal more.  In fact, intuition leads me to believe that companies with significant competitive advantages (moats) and high barriers to entry are often more risky, since the loss of these competitive advantages will cause a much greater loss in value than for companies that are expected to tread water and earn close to their cost of capital.

          Risk and Discount Rates
          When valuing companies, you confront all kinds of risk, some related to the company and some to the macro economy, some continuous and some discrete. In my post on uncertainty, I broke risks down in different categories and the way you incorporate risk into value can depend on the type of risk.  While it does seem intuitive to use the discount rate as the receptacle for all the risks that you are exposed to, it does not work very well. The reason is simple. A DCF is a going concern concept and the discount rate is designed to capture risks to a going concern, i.e., risks that cause revenues, earnings and cash flows to change over time but not truncation risk, i.e., risks that can cause an end to a company’s life. If you add on the perspective of a diversified investor looking at the going concern, the risk that is incorporated into a discount rate should only be macroeconomic risk that affects the value of the firm as a going concern and neither truncation risk nor micro/estimation risk has a place in value.

          So what should be done about risks like nationalization risk or distress risk? While your discount rate may be ill-equipped to convey theses risk, they should have an effect on value and I borrow a tool from probability & statistics to capture this effect.
          Decision Trees and Truncation Risk

          By attaching a probability to the truncation risk and calculating the consequence, you will reduce your expected value for an asset without doing discount rate gymnastics. That is the technique that I would use to value a start-up (with a high risk of failure), a young biotech company (where the failure to get drug approval can cause it to shut down) or even a large bank with a regulatory capital problem and the possibility of an equity wipeout (see my Deutsche Bank valuation from a couple of weeks ago). If you are interested in extending your probabilistic arsenal, try this paper that I have on the topic.



          What about company specific and estimation risk? Uncomfortable though it may make you to do so, when valuing public companies that are at the margin priced by institutional and diversified investors, you should let these risks pass through and use diversification as your tool for averaging risk. As for the oft-touted advice that the cash flows should be adjusted for risk, I would advice caution since many people who offer this advice seem to think that estimating cash flows across many scenarios and taking an expected value across them is adjusting for risk. It is not!

          The Distractions
          In any discussion of discount rates, distractions abound that can lead you not only away from good sense but very quickly into a morass. Here are two of the most common:

          • Margin of Safety: Many investors tout the margin of safety as their protection against risk. While I have absolutely no issue with building in a margin of safety into your investment decisions, as long as you recognize that there is a cost to being too conservative, I do not believe that it can be offered as an alternative to risk-adjusting the discount rate. As I understand it, the margin of safety is the buffer you build between value and price to protect yourself against your mistakes. If you are using a DCF to estimate value, you still need a risk-adjusted discount ate.
          • Homework: When doing valuation, I have been sometimes told that the reason that I face risk is because I have not done my homework, and that spending more time understanding the company, its business and the management will make the risk go away. Really? So, when valuing a Brazilian company, all I have to do is spend more time with the numbers and Brazil's political and economic uncertainties will magically vanish? I don't think so!
          • "Warren Buffett says": I have been told that Warren Buffett not only abhors the use of betas in valuation (but I dealt with that concern in Myth 4.2) but uses the risk free rate as his discount rate in valuing companies. Before you jump to the conclusion that he does not adjust for risk, I believe that his way of adjusting for risk is to count only that portion of a company's earnings that is predictable. In effect, he is using what I would call "certainty equivalent" cash flows. That approach may work reasonably well with mature companies but will quickly break down for growth companies.
          You can always choose another tool for estimating intrinsic value, but if you use a discounted cash flow valuation to estimate value, you have to estimate expected  cash flows, adjust the discount rate for going concern risk and arrive at a value.

          Conclusion
          When doing discounted cash flow valuation, the discount rate exerts a pull on analysts, inviting them to use it as a receptacle for their hopes and fears. Doing so will expose you to double counting both the good stuff (great management, strong moats) and the bad ones (exposure to catastrophic risk, concerns about uncertainty). The discount rate, at least in a DCF, is meant to carry the weight of measuring going-concern risks and that too from the perspective of the marginal investors in the company. That is task enough and it is best not to load it up with much more!

          YouTube Video



          Attachments
          1. Probabilistic Approaches: Simulations, Decision Trees and Scenario Analysis
          DCF Myth Posts
          Introductory Post: DCF Valuations: Academic Exercise, Sales Pitch or Investor Tool
          1. If you have a D(discount rate) and a CF (cash flow), you have a DCF.  
          2. A DCF is an exercise in modeling & number crunching. 
          3. You cannot do a DCF when there is too much uncertainty.
          4. It's all about D in the DCF ( Myths 4.14.24.3, 4.4 & 4.5)
          5. If most of your value in a DCF comes from the terminal value, there is something wrong with your DCF.
          6. A DCF requires too many assumptions and can be manipulated to yield any value you want.
          7. A DCF cannot value brand name or other intangibles. 
          8. A DCF yields a conservative estimate of value. 
          9. If your DCF value changes significantly over time, there is something wrong with your valuation.
          10. A DCF is an academic exercise.

          Myth 4.5: DCFs break down with near-zero risk free rates!

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          In any version of a risk and return model for discount rates, where you start with a riskfree rate as a base and build up to costs of equity, debt and capital, it seems blindingly obvious that as interest rates go lower, discount rates will follow and that value will increase. It is this logic that has led to the hand wringing about how central banks have both created pricing bubbles and made discounted cash flow valuations implode by “lowering’ rates. In a recent article, Sanford Bernstein proclaimed DCF all but dead in a world with near-zero risk free rates, because as they see it, the resulting low discount rates were pushing up the value of future cash flows, and since these cash flows are inherently more difficult to estimate, DCFs were less reliable. I have no problem with Bernstein's equity research analysts abandoning DCF and switching to pricing stocks instead, but I believe that they need to do for the right reasons, not the ones outlined in that thought piece.

          Risk free Rates in a Static World
          A few months ago, I posted on the hubris of central bankers who (a) believe that they control the level of interest rates and (b) that by changing the level of rates, they can affect stock/bond prices as well as real investments at companies. It is this misguided view of the world that, in my view, has given us years of ever-lower central banking rates, without the promised for results (of more capital investment and higher real growth). It is instructive that almost a decade into quantitative easing, the global economy still seems to be struggling to find its footing. 


          Unfortunately, this delusion that you can change the risk free rate and leave all else in the process unaffected is not restricted to central bankers and seems to have spread like a virus among valuation analysts, leading to many following the Bernstein script and abandoning DCF. The mathematics are impeccable. If you leave risk premiums (equity risk premiums and default spreads) unchanged, hold on to old growth rates and lower just the risk free rate, you will see value increase as the risk free rate increases and perhaps approach infinity at really low or negative risk free rates.

          To see why, let's assume that you had valued a company in 2007, when the risk free rate was close to 4% and the equity risk premium was also 4% and that you had assumed that this company's cash flow to equity, $100 million in the most recent year, would grow at 10% a year for the following five years and 4% thereafter. The value that you would obtain in a DCF would be $3.378 billion. Now assume that you have been revaluing the company every year in the years since, keeping the rest of your parameters fixed and changing just the risk free rate. As the risk free rate has dropped to levels not seen in recent history, your valuations will have zoomed:
          Download spreadsheet
          Your value of this company increase from $3.4 billion to $9.1 billion , as the risk free rate dropped to 1.5%, and lowering the risk free rate further will only increase value. In fact, at a 0% risk free rate (which is where the Euro and the Swiss Franc are at in November 2016), your valuation would approach infinity. As an added feature, as your risk free rate decreases, a greater proportion of your value comes from the terminal value, accounting for almost 94% of your value at a 1.5% risk free rate compared to 84% of value at a 4% risk free rate. That is the crux of the Bernstein argument against DCF, with the twist that estimating future cash flows is always difficult and that lower risk free rates have tilted valuation towards cash flows even further into the future. 

          Risk free Rates in a Dynamic World
          Let's get real. When risk free rates change substantially, it is not because central banks will them  to be lower or higher, but because of shifts in the fundamentals, and those shifts will affect your other inputs into valuation. In this section, I aim to start by showing how changing risk free rates affect growth rates and risk premiums and then argue that the value effect of a change in the risk free rate can be complicated (as market watchers have found out over the decades).

          Risk free Rates and Growth (Real and Nominal)
          If you have read my prior posts on interest rates and central banks, one of my favorite tools for understanding interest rates is the Fisher equation, which breaks down a riskless rate into two components: an expected inflation rate and an expected real interest rate. Using a proxy of real GDP growth for the real interest rate, I derive an "intrinsic" risk free rate as the sum of the inflation rate and real GDP growth. I may be stretching but it works surprisingly well at explaining why interest rates move over time, as evidenced in the graph below, where I compare the T.Bond rate to the sum of inflation and GDP growth each year from 1954 to 2015.
          So, what's the point of this graph? In addition to emphasizing the fact that central banks can affect rates only at the margin, it brings home the reality that low interest rates are indicative of a market that expects both inflation and real growth to remain low. It is entirely possible that the market is wrong but if you are doing valuation, you cannot selectively override the market on one variable (growth in the static example) while holding on to it on the other (risk free rate). 
          Dynamic Implication: As the risk free rate changes, your estimates of nominal growth will have to be stepped down, not because you have changed your beliefs about a specific company, but because you should be lowering the base growth rate for the economy (global or domestic).

          Risk free Rates and ERP
          The second variable that goes into play when risk free rates change is the equity risk premium. Again, you have to let go of the notion that equity risk premiums are static numbers that come out of historical data but are reflections of market worries about the future and investor risk aversion. Not surprisingly, the same forces that cause interest rates to move also affect the market's perception of risk and will cause equity risk premiums to shift. This can be seen when you look at implied equity risk premiums, where you back out what the market is demanding as an expected return on stocks from cash flows and subtract the risk free rate. In the graph below, I outline this effect since 2008.

          The most striking finding, at least for me, is how little the expected return on stocks has changed since 2008, staying around 8%, while risk free rates have more than halved. The net effect is that the equity risk premium, close to 4% prior to 2008, has now moved to 6% and above. 
          Dynamic Implication: As the risk free rate changes, the equity risk premiums you use will also have to change to reflect the market's updated expectations. A crisis that causes rates to plummet will also make risk premiums rise. If you stick with historical risk premiums, while using current risk free rates, you will misvalue companies.

          Risk free Rates and Default Spreads
          The same forces that cause equity risk premiums to rise as risk free rates drop also come into play in the bond market in the form of default spreads on bonds. In the graph below, I estimate the default spread on a Baa rated bond by comparing the Baa bond rate to the T.Bond rate each year from 1960 to 2015.
          As with the equity risk premium, default spreads have widened since 2008, from 2.02% in 2007 to 3.23% in 2015. 
          Dynamic Implication: As the risk free rate changes, the default spread used to estimate the cost of debt should also change, thus ensuring that the cost of debt will not move in lock step with the risk free rate.


          Risk free Rates and Debt Ratios
          To complete the story, the final ingredient that you need for the cost of capital estimation is a debt to capital ratio in market value terms. If as risk free rates change, both the equity risk premium and default spread also change, it should come as no surprise that the relative benefits of using one (debt0 over the other (equity) will also shift. To chronicle these change, I looked at the aggregate debt to capital ratios, in market and book value terms, for all US stocks, each year from 2000 to 2015.
          If you divide the time period into pre-2008 higher risk free rate and post-2008 lower risk free rate sub periods, it seems quite clear that US companies are borrowing more money than they used to. The facile explanation is that this is exactly what you would expect with lower interest rates but remember that those lower rates feed into both the cost of equity and debt. This effect is a more subtle one and reflects the relative risk premiums for equity and debt, perhaps suggesting that the price of equity risk has risen more than debt risk. 
          Dynamic Implication: As the risk free rate changes, the debt ratios for companies will also change as they reevaluate the trade off of using debt as opposed to equity. That change, in conjunction with tax and default risk assessments, will lead to a change in the cost of capital.

          Risk free Rates and Value: The Full Picture
          Now that we have a fuller picture of how risk free rates are interconnected to risk premiums and growth rates, let me revisit the example that I initiated in the static world of valuing equity in a company with a base year cash flow to equity of $100 million. Rather than let the growth rates and the risk premiums stay unchanged, here is what I assumed:
          • The nominal growth rate in the economy will be equal to the risk free rate, reflecting how closely the T.Bond rate has tracked the nominal GDP growth rate.
          • The company will grow at a rate 6% higher than the nominal growth rate of the economy for the next five years. Thus, with a 4% riskfree rate, the growth rate is 10%, matching the original assumption, but at a 2% riskfree rate, the nominal growth in cash flows will be 8%. In perpetuity, the company will now grow at the riskfree rate = nominal growth rate of  the economy,
          • The equity risk premium is the trickiest component, but if the market's behavior over the last decade is any indication, the expected return on stocks will stay at 8%, with the equity risk premium adjusting to the new risk free rate. Thus, if the riskfree rate drops to 2%, the equity risk premium will be 6%.
          The effect on value of changing the growth rate is captured in the picture below:
          Download spreadsheet
          Note that the neither the value nor the percentage of the value from terminal value change much as the risk free rate drops; in fact, they both decline marginally. Furthermore, I can now explore the effect on value of having a zero or negative riskfree rate and it is benign.

          I can only give you my personal perspective on how lower interest rates have affected my valuations. With lower rates, contrary to the Bernstein thesis, I find myself less worried about terminal values and the assumptions that I might have made incorrectly. When my nominal growth rate in perpetuity is capped at 2%, 1% or even 0%, I can do far less damage with my assumptions about what a firm can do in perpetuity, than I did in 2007. If anything, low risk free rates makes my intrinsic valuations less volatile, not more so. It is true that these are dangerous times for auto-pilot DCFs where a combination of inertia, trust in historical data (on risk premiums and growth rates) and failure to check for internal consistency can lead to explosively bad DCFs. If Bernstein's point is that a good pricing (based upon multiples and comparable firms) is better than an auto-pilot DCF, I am in agreement!

          Playing Devil's Advocate
          If you are skeptical about my arguments, I don't blame you! In fact, I will preempt you and bring up some counter arguments that you can make against my thesis.
          1. Mean Reversion: The essence of mean reversion is that when something looks unusually low or high, it will be revert back to historic norms. Using this argument on risk free rates, there are some who use "normalized" risk free rates (with the extent of normalization varying across users) in valuation. There are two problems with this argument. The first, and I referenced it in a different context in my post on CAPE, is that assuming things will revert back to the way they used to be can be dangerous, if there has been a structural shift in the process. The second, and perhaps even stronger, argument is that you cannot selectively mean revert some numbers and not mean revert others. Thus, if you decide to replace today's risk free rate with a normalized risk free rate of 4%, reflecting 2007 levels, you have to also adjust your growth rates and risk premiums to reflect 2007 levels. In effect, you will be valuing your company in 2016, as if your were back in 2007. Good luck with that!
          2. Central Bank as Master Manipulators: The conventional wisdom is that the Fed (and central banks) are all-powerful and that the low rates of today have little to do with fundamentals and more to do with central banking policy. If you believe that and you also believe that markets are being led by the nose, you do have the basis for a "bubble" argument, where "artificially" low interest rates are leading all financial assets into bubble territory. The problem, though, is that if this were the case, the cost of equity should be tracking down, in step with the risk free rate, and as the figure on equity risk premiums (in the section above) notes, that does not seem to be the case. 
          That is not to say that I am sanguine about low interest rates. The low growth and low inflation that these numbers signal are having their effect on companies. Real investment has declined, cash flows to investors (in dividends and buybacks) have increased and cash balances have surged. The increase in debt at companies will not only increase default risk but make these companies more sensitive to macro economic shifts, with more distress and default coming in the next downturn. Finally, to the extent that central banks send signals about the future, the desperation that is being signaled by their policies does not evoke much confidence in them. 

          Conclusion
          The risk free rate is an input into a discounted cash flow valuation but it is not an input that can be changed in isolation. When risk free rates change, they reflect shifts in fundamentals that should also show up in risk premiums and growth rates, making any resulting change in value difficult to forecast. As the hysteria mounts ahead of the next FOMC meeting, my suggestion is that you step back and take a big-picture perspective. This too shall pass!


          YouTube Video


          Attachments
          1. Risk free rates, Inflation and GDP Growth
          2. Risk free rates and ERP
          3. Risk free rates and the Baa Default Spread
          4. Risk free rates and Debt Ratios over time
          5. Static and Dynamic Valuation Spreadsheet
          DCF Myth Posts
          1. If you have a D(discount rate) and a CF (cash flow), you have a DCF.  
          2. A DCF is an exercise in modeling & number crunching. 
          3. You cannot do a DCF when there is too much uncertainty.
          4. It's all about D in the DCF (Myths 4.14.24.34.4 & 4.5)
          5. If most of your value in a DCF comes from the terminal value, there is something wrong with your DCF.
          6. A DCF requires too many assumptions and can be manipulated to yield any value you want.
          7. A DCF cannot value brand name or other intangibles. 
          8. A DCF yields a conservative estimate of value. 
          9. If your DCF value changes significantly over time, there is something wrong with your valuation.
          10. A DCF is an academic exercise.

          The Trump Effect on Markets: A Financial (not a Political) Analysis!

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          I have political views, but I try to keep them out of my classes and my blog posts. I teach and write about corporate finance/valuation, not political science, and I don't think it is fair to subject my students or readers of this blog to my views on politics. I would be committing malpractice, though, if I avoid talking about Tuesday's election, since it does have consequences for investing. That said, I know that nerves are exposed and emotions are raw and I want (perhaps unsuccessfully) to stay away from the hot-button issues and focus, as best as I can, on the investment implications of a Trump Presidency. As I started writing, I realized that I was repeating almost word for word what I had written in June, after UK voters voted for Brexit. Consequently, I decided to go back and copy the Brexit post, change "Brexit" to "Trump Election", to see how close they were.  The changes are in red and the replaced words are crossed out. You can be the judge on the parallels!

          There are few events that catch markets by complete surprise but the decision by British US voters to leave the EU elect Donald Trump as President comes close. As markets struggle to adjust to the aftermath, analysts and experts are looking backward, likening the event to past crises election surprises and modeling their responses accordingly. There are some who see the seeds of a market meltdown, and believe that it is time to cash out of the market. There are others who argue that not only will markets bounce back but that it is a buying opportunity. Not finding much clarity in these arguments and suspicious of bias on both sides, I decided to open up my crisis survival kit, last in use in August 2015, in the midst of another market meltdown.

          The Pricing Effect
          I am sure that you have been bombarded with news stories about how the market has reacted to the Brexit vote Trump Election and I won't bore you with the gory details. Suffice to say that, for the most part, it has not followed the crisis rule book: Government bond rates in developed market currencies (the US, Germany, Japan and even the UK) the United States have dropped risen, gold prices have risen stayed flat, the price of risk has increased decreased and equity markets have declined risen. The picture below captures the fallout of the vote across markets:
          As the election results came out on Tuesday night, the immediate market reaction was dire, with Dow futures dropping almost 800 points, triggering circuit breakers. By Wednesday morning, though, the panic seemed to have subsided and the market effect in the two days since the election have been not just benign, but positive. I know that it is early and that much can happen in the next few weeks to spook markets again, but as things stand now, here is what we see. Rates on US treasuries have risen sharply, with interpretations varying depending upon your election priors, with those negatively inclined to Trump viewing the rise as a sign that foreign buyers are pulling out the market, leery of his comments about  and those positively inclined arguing that the rise reflects expectations of higher growth in the future. The dollar has held its own against other currencies and the fear indices (gold and the VIX) have fallen since Tuesday, with the VIX dropping dramatically. US stocks have risen in the two days since the election, with small cap stocks in Russel 2000 rising more than the large cap stocks. If you are puzzled by the NASDAQ's inability to join the rally, you can see why when you look at the returns across the S&P sectors:

          Last 5 daysLast 3 monthsYTD (2016)
          Consumer Discretionary2.46%-2.57%1.05%
          Consumer Staples-0.88%-4.97%2.95%
          Energy3.80%3.50%16.79%
          Financial Services6.48%7.46%6.38%
          Financials6.71%6.70%7.77%
          Health Care6.20%-5.36%-1.74%
          Industrials5.59%2.23%12.58%
          Materials4.39%-0.94%11.15%
          Real Estate0.40%-12.21%-3.83%
          Technology1.37%0.45%10.55%
          Utilities-1.17%-6.59%9.43%
          S&P 5003.11%-0.85%5.84%
          The stock market rise in the last few days has been uneven with consumer staples, utility, technology and real estate stocks (ironically) lagging and financial firms, health care and industrials doing well. Though it is dangerous to try to create full-blown stories based on stock market behavior over a few days, it seems likely that the rally in financials and pharmaceuticals can be traced as much to expectations about what Trump has said he will do (repeal Obamacare, for instance) as to relief that some of the regulations/restrictions that Clinton had proposed (on pharmaceutical pricing and more constraints on banks) would not longer be on the table. The decline in utilities can be attributed to rising interest rates but the swoon in tech stocks bears watching, since it could be an indication that tech companies, who strongly backed Clinton, may face headwinds in a Trump administration. 

          The Value Effect
          As markets make their moves, the advice that is being offered is contradictory. At one end of the spectrum, some are suggesting that Brexit Trump election could trigger a financial crisis similar to 2008, pulling markets down and the global economy into a recession, and that investors should therefore reduce or eliminate their equity exposures and batten down the hatches. At the other end are those who feel that this is much ado about nothing, that Brexit will not happen or that the UK will renegotiate new terms to live with the EU and that investors should view the market drops as buying opportunities the Trump effect can be more positive than negative, with changes in taxes and regulations offsetting any negative consequences from his trade policies. Given how badly expert advice served us during the run-up to Brexit the Trump election, I am loath to trust either side and decided to go back to basics to understand how the value of stocks could be affected by the event and perhaps pass judgment on whether the pricing effect is under or overstated. The value of stocks collectively can be written as a function of three key inputs: the cash flows from existing investment, the expected growth in earnings and cash flows and the required return on stocks (composed of a risk free rate and a price for risk).  The following figure looks at the possible ways in which Brexit the Trump presidency can affect value:


          I know the perils of assuming that campaign promises and rhetoric will become policy, but broadly speaking, you can outline the possible consequence for companies of Trump's proposed policy changes. The biggest and potentially most negative effect would come from his trade policies, where protectionist policies can and will draw protectionist responses from other countries, putting global trade and growth at risk. Trump has been ambivalent about both the Federal Reserve's interest rate policies and financial markets, arguing that the Fed has played politics with interest rates and that financial markets are in bubble territory. It will be interesting to see whether the FOMC, when it meets in January, takes into account the election results, in making its widely telegraphed decision to raise rates (at least the ones that it controls). Trump has proposed major changes to both corporate and individual tax rates, and if Congress goes along even part way, you can expect to see a lower corporate tax rate accompanied by inducements to bring the $2.5 trillion in trapped cash that US companies have in other markets.

          There is also likely to be sector-specific fall out from other Trump policies, at least in contrast to what these sectors would have faced under a President Clinton. President Trump has prioritized repealing Obamacare and that will have direct consequences for companies in the health care sector, with some benefiting (pharmaceutical companies?) and some perhaps being hurt (insurance companies and hospital stocks?). President Trump's proposal to invest heavily in the nation's infrastructure will benefit the construction, engineering and raw material firms that will construct that infrastructure but he may run into both budgetary constraints (with his tax proposals) and political headwinds (from conservatives in Congress). Finally, President Trump has promise to reduce regulation on business and put in more business-friendly regulators on the regulatory bodies and that will be viewed as good news by banks and fossil-fuel firms that were facing the most onerous of these regulations. The Trump proposals to preserve the entitlement programs, lower taxes and increase infrastructure spending are potentially at war with each other and budget constraints, but that does not mean that significant parts of each one will not become law.

          In evaluating these possibilities, I am cognizant of the checks and balances that characterize the US system. Unlike parliamentary systems, where a new government can quickly  rewrite laws and replace old policies, the framers of the US constitution put in a system where power is shared by the executive, the legislature and the courts, making change difficult. Even with Republicans controlling the executive and legislative branches, I am sure that Trump supporters will be frustrated by how slowly things move through the mill and how difficult it is to convert proposals to policies and Trump detractors will learn to love the same filibusters, congressional slowdowns and legal roadblocks that they have inveighed against over the last eight years. 

          The Bigger Lessons
          It is easy to get caught up in the crisis of the moment but there are general lessons that I draw from Brexit the Trump election that I hope to use in molding my investment strategies.
          1. Markets are not just counting machines: One of the oft-touted statements about markets is that they are counting machines, prone to mistakes but not to bias. If nothing else, the way markets behaved in the lead-up to Brexit the election is evidence that markets collectively can suffer from many of the biases that individual investors are exposed to. For most of the last few months, the British Pound Mexican Peso operated as a quasi bet on Brexit the US presidential election, rising as optimism that Remain Clinton would prevail rose and falling as the Leave Trump campaign looked like it was succeeding. There was a more direct bet that you would make on Brexit Trump in a gamblers' market, where odds were constantly updated and probabilities could be computed from these odds. Since Brexit the US election was also one of the most highly polled in history, you would expect the gambling to be closely tied to the polling numbers, right? The graph below illustrates the divide. 

            While the odds in the Betfair did move with the polls, the odds of the Leave camp Trump winning never exceeded 40% in the betting market, even as the Leave camp acquired a small lead in the weeks leading up to the vote the polls got closer in mid-September and in the last week before the election. In fact, the betting odds were so sticky that they did not shift to the Leave side until almost a third of the votes had been counted Trump until late on Tuesday night. So, why were markets so consistently wrong on this vote? One reason, as this story notes,  is that the big bets in these markets were being made by London-based bigger investors tilting the odds in favor of Remain Clinton. It is possible that these investors so wanted the Remain vote Clinton to win that they were guilty of confirmation bias (looking for pieces of data or opinion that backed their view). In short, Brexit Trump reminds us that markets are weighted, biased counting machines, where big investors with biases can cause prices to deviate from fair value for extended periods.
          2. No one listens to the experts (and deservedly so): I have never only once before seen an event where the experts were all so collectively wrong in their predictions and so completely ignored by the public. Economists, foreign policy experts and central banks opinion leaders all inveighed against exiting the EU Trump, arguing that is electing him would be catastrophic, and their warnings fell on deaf years, as voters tuned them out. As someone who cringes when called a valuation expert, and finds some of these experts to be insufferably pompous,  I can see why experts have lost their cache. First, in almost every field , expertise has become narrower and more specialized than ever before, leading to prognosticators who are incapable of seeing the big picture. Second, while experts have always had a mixed track record on forecasting, their mistakes now are not only more visible but also more public than ever before. Third, the mistakes experts make have become bigger and more common as the world has become more complex, partly because the interconnections between variables means there are far more uncontrollable elements than in the past. Drawing a parallel to the investment world, even as experts get more forums to be public, their prognostications, predictions and recommendations are getting far less respect than they used to, and deservedly so. Finally, it is time that we that are open about the fact that we are all biased and being smart or an expert does not immunize from bias.
          3. Narrative beats numbers: One of the themes for this blog for the last few years has been the importance of stories in a world where numbers have become more plentiful. In the Brexit debate US presidential election, it seemed to me that the Leave side Trump had the more compelling narrative (of a return to an an old Britain America that enough voters found appealing to help him win) and while the Remain side Clinton argued that this narrative was not plausible in today's world, its counter consisted mostly of numbers (the costs that Britain would face from Brexit) inveighing against Trump's character and temperament. Looking ahead to similar referendums elections in other EU countries,  I have a feeling that the same dynamic is going to play out, since few established politicians in any EU country seem to want to make a full-throated defense of being Europeans first the status quo
          4. Democracy can disappoint (you): The parallels between political and corporate governance are plentiful and Brexit this election has brought to the surface the age-old debate about the merits of direct democracy. While many, mostly on the winning side, celebrate the wisdom of crowds, there are an equal number on the losing side who bemoan the madness and prejudices of crowds.  As someone who has argued strongly for corporate democracy and against entrenching the status quo, it would be inconsistent of me to find fault with the British American public for voting for Brexit Trump.  In a democracy, you will get outcomes you do not like and throwing a tantrum or threatening to move are not democratic responses.  You may not like the outcome, but as an American political consultant said after his candidate lost an election, "the people have spoken... the bastards".
          The End Game
          I am sure that reading this post, with its crossed-out words and red insertions, has been tiresome, but I also think that the parallels between what happened around Brexit and the US presidential election are too strong for this to be coincidence. Just as technology and social media are upending traditional models in businesses, these two elections are signaling a change in the political game and it is not just politicians, pollsters and political consultants who should be taking notice.

          YouTube Video

          Family Feuds: The Promise and Peril of Family Group Companies!

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          I teach a corporate finance class, a class that I describe as big-picture (since it covers every aspect of business), applied and universal in its focus. I use six firms, ranging the spectrum from large to small, developed (Disney & Deutsche Bank) to emerging (Vale & Baidu) and public to private (a privately owned bookstore in New York), as lab experiments to illustrate both corporate finance first principles and financial models/theory. One of my illustrative companies is Tata Motors, an India-based auto company, to illustrate the special challenges associated with managing and investing family group companies, where the conflict between what’s good for the family group and for the company can play out in every aspect of corporate finance. I picked a Tata group company for a simple reason; among Indian family groups, it is among the most highly regarded, and my intent was to show that even in the best run family group companies the potential for conflict lies just under the surface and events over the last few weeks has added weight to that argument.

          The Tata Group, the Enlightened Family Group?
          It is not hyperbole to say that the Tata family and Indian business have been for much of the last two centuries. The first Tata company came into being in 1868 and it was built up incrementally and often through difficult times to become the behemoth that it is today. Along the way, it spread itself across many businesses, creating what would have been a classic conglomerate, if it had stayed as one company. In typical family group style, though, it chose to pursue each business with a separate entity and by 2016, the group included more than 100 companies, with 29 of these being publicly traded, stand-alone entities. The picture below captures the company's holdings and control structure in 2016:

          Note how the companies are all bound together by Tata Sons, which, in turn, is controlled by the Tata trusts, holding close to 66%, with power lying with the Tata family. As a side note, the largest non-Tata stockholder is the Shapoorji Pallonji Group, which control 18.4% of Tata Sons. While each publicly traded company in the group is an independent entity, with a CEO and a board of directors (with a fiduciary responsibility to protect the shareholders of that company), the independence is illusory. Not only does Tata Sons own a significant piece of each company, the companies all own shares in each other (cross holdings effectively controlled by the family group) and directors representing family group interests serve on each board. Note that though is much is made of the conglomerate nature of the Tata Group, the group derives the bulk of its value (>70%) from TCS, a technology company that derives most of its revenues from outside India. It is a testimonial to the stability and continuity in the Tata Group that it has had only six men at its helm over its 150-year history:

          ChairmanTenureHighlights
          Jamsetji Tata1868-1904Founded the Tata Group as a trading company in 1868.
          Dorab Tata1904-1932Instrumental in creating the Tata Trust, the family philathropy
          Nowroji Saklatvala1932-1938Related to the Tatas and started profit-sharing scheme.
          JRD Tata1939-1991Legendary and longest-serving CEO and a pioneer in civil aviation.
          Ratan Tata1991-2012Presided over global expansion of the group, acquiring global companies to do so.
          Cyrus Mistry2012-2016Related to Tatas and son of one of the Tata group's largest stockholders.
          JRD Tata who presided over the company for a large portion of the last century was legendary, not just for his business acumen but his social consciousness and was viewed as India’s most upstanding corporate citizen. In fact, Cyrus Mistry who became chairman of Tata Sons in 2012, was more insider than outsider, backed by Shapoorji Pallonji Group, as a scion of the family (behind that group) and also related by marriage to the Tata family. 

          This history of stability is perhaps why investors and onlookers were shocked by the events of the last few weeks. On October 24, 2016, the board of directors of Tata Sons fired Cyrus Mistry as the Chairman of Tata Sons for non-performance, a failure to deliver on promises. Mr. Mistry did not go quietly into the night and fought back, arguing that not only was the removal not in keeping with Tata traditions of decorum and fairness, but that his removal was effectively a coup by old-time Tata hands who were threatened by his attempt to clean up mistakes made by prior regime (headed by Ratan Tata). In particular, he argued that many of the high-profile acquisitions/investments that Mr. Tata had made, including those of Corus Steel (by Tata Steel) and forays into the airline business (Vistara and AirAsia) were weighing the company down and that it was his attempts to extract Tata companies from these messes that had provoked the backlash. Defenders of the removal argued that Mr. Mistry had been removed for just cause and that his numbers-driven (and presumably short-term) decisions were not in keeping with the Tata culture of building businesses for the long term.

          The opacity that surrounds the Tata companies with their incestuous corporate governance structures (with directors sitting on multiple Tata companies) and complex holding structures makes it difficult to decipher the truth, but the two sides seems to be in surprising agreement on one point, that the bulk of the value of the Tata Group derives from two investments, TCS and Jaguar Land Rover. In fact, the area of disagreement is about why rest of the group was in in trouble and what should have been done about them. The Mistry camp argues that the troubles at the rest of the group can be traced back to ill-advised and expensive acquisitions (Corus, Tetley) and investments (Nano) made during the Tata tenure and the Tata camp suggests that Mr. Mistry knew about those problems when he was hired and that he did little to fix them during the  four years of his tenure. Whatever the truth, the company has a mess on its hands. While Mr. Mistry has been forced out at Tata Sons, he remains on the boards of the other publicly-traded Tata companies and was chairman of the board at TCS until a couple of days ago. That sets the stage for a war of attrition, which cannot be good news for any Tata company stockholder or for either side in this dispute, since they both have substantial stakes in the group.

          The more general question raised by this episode is a troubling one. If a corporate governance dispute of this magnitude can occur at a family group that many (at least on the outside) viewed as one of the least conflicted in India, and you and I, as stockholders in Tata companies, can do nothing but watch helplessly from the outside, what shred of hope can we have of being protected at other family groups that are much more open about putting their interests over that of stockholders? I remember being asked after I had completed a valuation of Tata Motors a few years ago whether I would buy its stock and shocking my audience by saying that I would never buy a Tata company for my portfolio. When pushed for my rationale, I said that buying a family group company is like getting married and having your entire set of in-laws move into the bedroom with you; in investment terms, if I invest in Tata Motors, I will (unwillingly) also be investing in many other Tata Group companies, because about 30-40% of the value of Tata Motors comes from its holdings in other Tata companies.

          The 4Cs of Family Businesses: The Trade off
          As an investor, I may not be inclined to invest in a family group company but it is undeniable that in much of Asia and Latin America, family group companies not only dominate the business landscape but have played a key role in economic development in the countries in which they operate. Consequently, there must be advantages they bring to the game that explain their growth and continued existence and here are a few:
          1. Connections: In many countries, including populous ones like India, influence is wielded and decisions are made by a surprisingly small group of people who know each other not just through their business networks but also through their social and family connections. These “people of influence” include bankers, rule makers and regulators that determine which businesses get capital, what rules get written (and who gets the exceptions) and the regulations that govern them. Family group companies have historically used these connections as a competitive advantage against upstart competition (both from within and without the country), especially in an environment where you have to pass through a legal, bureaucratic and political thicket to start and run a business. 
          2. Capital: Extended family group companies create internal capital markets, where profitable and mature companies in the group can invest their excess cash in growth companies within the same group that need the capital to grow. This works to their advantage, especially when external capital markets (stock and bond) are illiquid and poorly developed and in countries that are susceptible to shocks (political or economic) that can cause markets to shut down.
          3. Control (Good): I have always taken issue with analysts who blithely add control premiums to the estimated values of target companies in acquisitions, not because I don’t think control has value but because I believe that to value control, you have to be specific about what you would change in the acquired company. Control is absolute in family group companies, sometimes because the families own controlling stakes in each of the companies in the group and sometimes because they have skewed the rules of the game in their favor (through opaque holding structures and shares with disproportional voting rights). In the benign version of this story, family groups use this control to make decisions that are good for the long term value of the company but that may be viewed negatively by “short term” investors in markets. Not having to pay attention to what equity research analysts write about their companies or look over their shoulders for hostile acquirers and activist investors may give family group companies advantages over their competitors who may be more vulnerable to these pressures.
          4. Culture (Good): A successful business is usually driven not just by quantitative objectives but also by a corporate culture that is unique and binds those who work at that business. In a non-family group company, that culture may come from the ethos of the top management of the company but is more susceptible to change than at a family-group company, where the family culture not only is much more pervasive but more long term. To the extent that the culture that is embedded is a good one, that can be a benefit to the company both in terms of retaining employees and customer trust.
          The research on family group companies is still in its nascency but the studies that I have seen seem to find strengths in these businesses, relative to conventional companies. That said, each of these advantages can very quickly be flipped to become disadvantages and here is that list:
          1. Connections -> Cronyism: I have no moral objections to building connections-based businesses, but if your primary competitive advantage becomes the connections that you possess, it is possible that you will rest on that advantage and not work on developing other core competencies. That will put you at a disadvantage when you go into foreign markets, where you don't have the connections advantage or when global competitors enter domestic markets. It is also true that as the connections shift from family and social ones to the political arena you are on more dangerous ground, since a change of regime (democratic or otherwise) can be devastating to your  business interests.
          2. Internal Capital -> Cross-subsidization and Cross-holdings: While there are advantages to letting the cash surplus companies in a family group fund those with cash deficits (and growth potential), there are two potential costs. The first is that, without the discipline of an external lender or equity market, investments in companies may not meet bare minimum corporate finance criteria. with intracompany loans made at below-market rates and intracompany equity investments generating returns on capital that are less than the cost of capital. That cross subsidization not only transfers wealth from your best companies to your worst but can collectively make the group worse off. The other is that these investments and how they are recorded in accounting statements make them more complex and difficult for investors to understand. Valuing a company with twenty cross holdings effectively requires you to value twenty one companies.
          3. Control (Good) -> Control (Bad): If the complete control that families have over family groups gives them the capacity to make long term decisions that are good for the company, in the face of market disapproval, that same complete control also can lock in the status quo, with inertia determining much of how it makes investment, financing and dividend decisions. Put differently, if a family is mismanaging a business, it can be very difficult to get it to change its ways.
          4. Culture (Good) -> Culture (Bad): The culture of the family can pervade the family group, but that culture can sometimes become an excuse for not acting or even acting badly for two reasons. First, a family culture can go from benign to malignant, more Gambino than Von Trapp, and having that culture pervade an organization can be deadly. Second, the implicit assumption that family members share a common culture may be an artifact of times gone by, as families splinter and go their own ways. In fact, it is not uncommon to see two siblings or even a parent and a child with very different perspectives on corporate culture battle for the future a family group.
          As you weigh the pluses and minuses of family groups, you can see why they developed as the dominant business form in Asia and Latin America over the last century. Many of the countries where family groups dominate have historically had rule and license driven economies with under developed capital markets (illiquid stock markets and state-controlled bankers). Protected in their domestic markets, family group companies have not only been able to grow but keep upstart competitors constrained. As these markets are exposed to globalization, though, and capital markets open up in these countries, the family group's advantages are declining but they are still entrenched in  many businesses.

          Back to the Tata Group
          If forced to invest in a family group company, I would take a Tata company over many other family group companies. The problem that I see in this latest tussle is less one of venality and more of a failure to adjust to the times and a clash of egos. Ratan Tata's global ambitions, manifested in a spate of acquisitions during his tenure, put the group into businesses and markets where their historical advantages no longer provide an edge. It is ironic that the two most successful pieces of the Tata group are Tata Consultancy Services, the company that is at odds with much of the rest of the Tata group in terms of focus and characteristics, and Jaguar Land Rover, a global luxury auto maker with a brand name that has little to do with the Tata family. I am sure that there is no shortage of advice being offered to the group at this time, but these would be my suggestions on what the group needs to do now.
          1. Settle (soon): The dispute between Cyrus Mistry and Ratan Tata has to be settled and soon. Nothing good can come from continuing to fight this out in public and both sides have too much to lose.
          2. This is personal: It seems to me that the fight has become a personal one, with managers and directors taking sides (voluntarily or otherwise) between Ratan Tata and Cyrus Mistry. That tells me that any rational solution will be tough to reach, unless both personalities withdraw from the fray. It seems to me that, for this crisis to abate, Ratan Tata has to step down as chairman and let a third party that both sides find acceptable step in, at least for the interim
          3. Separate the public companies from the private: If this episode shows the danger of tying together all of the Tata companies to Tata Sons and the family group, the first step in untangling them is to separate the 29 public companies from the private companies in the group. The dangers of self dealing and conflicts of interest are greatest when the private businesses interact with the public companies.
          4. Unit Independence: The next step in this process is to make each public company truly independent and that will require (a) selling cross holdings in other Tata companies and (b) removing family group directors who serve on the boards of the stand alone companies.
          5. Restrict intra group activities: It would be impractical and perhaps even imprudent to bar Tata companies from interacting with each other, but those interactions should follow first principles in finance. Hence, while intra-group loans may sometimes make sense, the interest rates on these loans should reflect the risk of the borrowing entity and intra-group equity investments should be value adding, i.e., earn a return on capital that exceeds the cost.
          6. Transparency: Disentangling cross holdings and restricting nitric will be a big step towards making the financial statements of the Tata companies more informative.
          Some of these changes can (and should) happen soon, but some may take a while to unfold but they have to be set in motion, with the recognition that the end game may be that some Tata companies, some with storied histories, may have to shrink or even disappear and that others will be elevated.

          Lessons for India Inc.
          For must of the last two decades, the lament in India is that China has beaten it handily in the global growth game. While it would be unfair to blame this on family group businesses, it is worth noting that the one sector where India seems to have move forward the most is technology and where it has fallen behind the most in in infrastructure and manufacturing. It may be coincidence that technology is the sector where, TCS notwithstanding, you have seen the most entrepreneurial activity and that traditional manufacturing is dominated by family group businesses. As India moves towards being a global player, opening up hitherto unopened sectors (like retail and financial services) to global players, the family group structures in these sectors may operate as handicaps.  While I don’t believe that it is the government’s place to insert itself within family groups, it should stop tilting the playing field in their favor by doing the following:
          1. Reduce the need for connections to do business: At the core of connection-driven business success is the existence of licenses and bureaucratic rules governing businesses. Reducing the licensing needs and the rules that govern how you run businesses will create a fairer business environment, though that may sometimes require governments to accept the result that a foreign company will win at the expense of a domestic competition
          2. Government-based or influenced investors (LIC) should be more activist: The largest stockholder in the Tata Group is the Life Insurance Corporation (LIC), a state-owned company, that has holdings in almost every large Indian company. For decades, LIC has chosen to back incumbent managers against activist investors and has allowed the woeful corporate governance at many family group companies to continue without a push back. 
          3. Banking/Family Group Nexus: Bankers, many government picked and influenced, have historically had cozy relationships with family group companies, lending money on projects with little oversight and often with implicit backing from the family group (rather than the company that is getting the loan). Those relationships not only give family group companies an advantage but are bad for banking health and need to be examined.
          Conclusion
          The turmoil at the Tata Group has all the makings of a soap opera and can be great entertainment if you are an armchair observer with no money in Tata company shares. It would be a mistake, though, to view this as an aberration because the palace intrigue and the infighting that you observe can not only happen in other family groups but take an even darker tone. To the extent that family group companies pushed their companies into public markets because they wanted to raise fresh capital and monetize their ownership stakes, they have to play by the rules of  the game

          YouTube Video


          Links
          1. My Corporate Finance Class (Spring 2016)

          References

          Faith, Feedback and Fear: Ready for the Valeant Test?

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          It is easier and more fun to write about your winners than your losers, but it is also far more important and valuable to revisit your losers, where the story has not played out the way you hoped it would. It is important because it is easy to lapse into denial and hold on to your losers too long, not only because you let hope override good sense but also because the act of selling is the ultimate admission that you made a mistake. It is valuable because you can learn from these mistakes, if you can set aside pride and preconceptions. So, it is with mixed feelings that I am returning to Valeant, a stock that I bought in May at $27, contending that it was worth $44, but where the market has clearly had other ideas. 

          Valeant: Revisiting the Past
          I first wrote about Valeant just over a year ago, when it was entering its dark phase, surrounded by scandals, management intrigue and operating problems. At the time, the stock had completed a very quick descent from market star to problem child, with its stock price (market cap) dropping from $180 on October 1, 2015 to $80 on November 6, 2015. While there were many in the value investing community, where it had been a long time favorite, who felt that the market had over reacted, my valuation of $77 left me just short of the market price of $80 at the time. Over the next few months, things went from bad to worse on almost every dimension. The management team disintegrated, with many of the top players leaving in disgrace, and the company held back on reporting its financials because it was having trouble getting its books in order, never a good sign for investors. Testimony by its top managers in front of congressional committee shredded its corporate character and the company faced legal challenges on multiple fronts. The market, not surprisingly, punished the stock as the company lurched from one crisis to another and the stock price dropped almost 75%:

          In May 2016, I revisited the company, just after it hired a new CEO (Joseph Papa) and Bill Ackman, a long-time activist investor in the company, decided to take a more active role in the company. In revaluing the company, I noted that the missteps at the company had hamstrung it to the point that it had during the period of a year made the transition from Valeant the Star to Valeant the Dog. The value that I estimated for the company, viewed as such, was $43.56.

          Download spreadsheet
          In keeping with my theme that the value of a company always comes from an underlying story, it is worth being explicit about the story that I was telling in this valuation. In May 2016, I viewed Valeant as a mature pharmaceutical company that would not only never be able to go back to its “acquisitive” days but was likely lose ground to other pharmaceutical companies with better R&D models. Consequently, in my valuation, I assumed low revenue growth and lower margins and a return on capital that would converge on the cost of capital over time. My decision in May 2016 was to buy Valeant at $27 because I felt that, notwithstanding the fog of missing information, management changes and legal sanctions, the company was a good buy. 

          The Market Speaks
          In the months since my buy in May 2015, there has been little to cheer about for Valeant investors. The stock had an extended swoon in late June, recovered somewhat in August, before continuing its descent in the last two months, with three possible explanations for the price performance. One is that the debt overhang, with $30 billion plus in debt due, making it the most highly levered company in the pharmaceutical business, creates market spasms each time worries about default resurface. In fact, every few weeks, another rumor surfaces of Valeant planning to sell a major chunk of itself (Bausch and Lomb, Salix) to remove the debt burden. The second is that the consolidation and cleaning up for past mistakes seems to be taking a lot longer than expected, with revenues stagnating and huge impairment charges pushing equity earnings into negative territory. The third is that the legal jeopardy that was triggered by the events of last year is showing no signs of abating, with the most recent news story about indictment of Valeant executive, Gary Tanner, and Philidor's Andrew Davenport  continuing the drip-drip of bad news on this front.

          For most of the last few months, as the price dropped, I have been waiting for something more concrete to emerge, so that I could revalue the company. On November 8, Valeant filed its most earnings report for the third quarter, reporting that revenues were down more for the third quarter of 2016 and larger losses than expected. It accompanied the report with forward guidance that suggested continued stagnation in revenues and no quick profit recovery next year, leading to a sell-off in the stock, pushing the price down to just below $14 on November 9. While I the reports is definitely not good news, I must confess that I did not see much in that report that was game or story changing. To see why, take a look at the numbers contained in the most recent earnings report:
          2016, Q32015, Q3Change2016, Q1-32015, Q1-3Change
          Revenues$2,480 $2,787 -11.02%$7,271 $7,689 -5.44%
          COGS$658 $649 1.39%$1,946 $1,855 4.91%
          S,G &A$661 $698 -5.30%$2,145 $1,957 9.61%
          R&D$101 $102 -0.98%$328 $239 37.24%
          Amort & Impair, finite-lived intangible assets$807 $679 18.85%$2,389 $1,630 46.56%
          Goodwill Impairment$1,049 $- NA$1,049 $- NA
          Acquisiton Costs (all)$67 $213 -63.93%$131 $648 -65.06%
          Operating Income$(863)$448 -292.63%$(716)$1,366 -152.42%
          EBIT pre-acquisition costs$(796)$661 -220.42%$(585)$2,014 -129.05%
          EBITDA$1,060 $1,340 -20.90%$2,853 $3,644 -21.71%
          EBITDAR$1,161 $1,442 -19.49%$3,181 $3,883 -18.08%

          It is true that the company is delivering lower revenues than the revenues that I had forecast for the company in May 2016 and it is also true that the company’s profit margins are dropping. However, and this may just be my confirmation bias speaking, as I look at the third quarter numbers, it seems like a significant portion the bad news reported for the quarter reflects repentance for past sins, not fresh transgressions. The company has had to respond to its “price gouger” reputation by showing restraint on further price increases (dampening revenue growth in its drug business) and the losses in the third quarter can be largely attributed to impairments of goodwill and assets acquired during the go-go days. In the table below, I break down the drop in operating income of $2.08 billion from the first 3 quarters of 2015 to the first 3 quarters of 2016 into it's constituent parts: 
          Effect on operating Income% Effect
          Declining Revenues$(317)15.27%
          Change in Gross Margin$(192)9.24%
          Change in SG&A$(188)9.05%
          Change in R&D$(89)4.29%
          Change in Acquisition Costs$517 -24.89%
          Change in Amortization (Assets + Goodwill)$(1,808)87.05%
          Change in Operating Income, , First 3Q 2016 vs First 3Q 2015$(2,077)100.00%
          The numbers suggest that almost 87% of the decline in operating income can be traced to amortization either of finite lived assets or goodwill, though there has been deterioration in the business model as manifested in the decline in sales and gross margins. It is for this reason that the effect this earnings report has had on my “Valeant as Dog” story is muted, largely because the story was not an uplifting one in the first place. My updated version of the story is that Valeant is not that different from my old one (of slow growth and lower margins) with tweaks for an upfront adjustment period where revenues are flat and margins worse than the past, as the company continues to slowly put its past behind it. The value per share that I get with this story is $32.50 and the picture is below:
          On November 8, 2016, with the stock price at about $15, it was the biggest loser in my portfolio but if I trust my own updated assessment of value of Valiant, it is now more undervalued (on a percent basis) than it was in May 2016. 

          Faith and Feedback
          In both my valuation and investments classes, I spend a significant amount of time talking about faith and feedback and how they affect investing.
          1. Faith: As an investor, you are acting on faith when you invest, faith in your assessment of value and faith that the market price will move towards that value. If you have no faith in your value, you will find yourself constantly revisiting your valuation, if the market moves in the wrong direction (the one that you did not predict) and tweaking your numbers until your value converges on the price. If you have no faith in markets, you will not have the stomach to stay with your position if the market moves against you. 
          2. Feedback: As an investor, you have to be open to feedback, i.e., accept that your story (and valuation) are wrong and that market movements in the wrong direction are a signal that you should be revisiting your valuation. 
          I view my investing challenge as maintaining a balance between faith and feedback since too much of one at the expense of the other can be dangerous. Faith without feedback can lead to doubling down or tripling down on your initial investment bet, blind to both new information and your own oversights, and that righteous pathway can lead to investment hell. Feedback without faith will cause an endless loop where market price changes lead you to revisit and change your value and your holding period will be measured in days and weeks instead of months or years.  Stocks like Valeant are an acid test of my balancing act. There is a part of me that is telling me that it is time to listen to the market, take my losses and sell the stock. However, doing that would be a direct contradiction of my investment philosophy and I am not quite ready to abandon it yet. The second is to avoid all mention of the stock and hope that the market corrects on its own, but denial is neither faith nor feedback. The third is to accept the fact that I did underestimate how long it would take Valeant to put its past behind it and to revalue the company with my updated story and that is what I tried to do. That acceptance of feedback, though, has to be accompanied by an affirmation of faith; since it led me to buy the stock at $27, when my estimated value was $43 in May 2016, it should lead me to buy even more at $15, with my estimated value at $32.50. So, I doubled my Valeant holdings, well aware of the many dangers that I face: that the operating decline that you saw in the third quarter of 2016 will continue in the future years, that the debt load will become more painful if interest rates rise and that the recent indictments of executives will expose the firm to more legal jeopardy. If the essence of risk is best captured with the Chinese symbol for crisis, which is a combination of the symbols for danger and opportunity, Valeant would be a perfect illustration of how you cannot have one without the other!

          YouTube Video


          Attachments

          1. Valeant - Valuation in November 2016

          Myth 5.1: If you don't believe in forever, you cannot do a DCF

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          If you are not interested in intrinsic valuation and feel that discounted cash flow valuation (DCF) is a waste of your time, you may want to skip these next few posts, which continue a series that I started more than two years ago on myths that surround DCF.  While these posts may strike you as esoteric and perhaps even obsessive, I wrote them for two reasons: these misconceptions lead to time-wasting debates among analysts and  they have economic consequences, costing business owners, investors and taxpayers large amounts of money. In these next few posts, I focus on the terminal value, which is, by far, the largest single cash flow in any discounted cash flow valuation.  As a consequence, it is not only the number that causes the most disagreement among analysts but it also remains the source for the most egregious errors in valuation.

          The Closure Factor
          To understand the role that a terminal value plays in a discounted cash flow valuation, let us revisit the equation that characterizes a DCF:
          Thus, for an asset with a life of n years, you would need to estimate cash flows for n years and then compute the present value of these cash flows, using a risk adjusted discount rate. That may not seem burdensome if you have an asset with a 5-year or even a 10-year life, but what if an asset is expected to last for 40 or 50 years, or in some cases, forever? When would the last scenario come into play? Consider the valuation of a publicly traded company, which at least in theory, could last forever. To value that business, you would need to estimate cash flows forever, a task that seems more designed for torture than for estimating value. In such cases, the analyst is granted a reprieve, by being required to estimate cash flows for a shorter window than the life of the asset and then applying closure by estimating a final cash flow that captures the value (at that point in time) of cash flows beyond. Thus, if you have an asset whose life is greater than n years and you estimate cash flows for only t years, you can rewrite the DCF equation as follows:
          The challenge that we face in valuation is in how best to estimate this terminal value.

          Three Acceptable Approaches to Estimation
          In presenting terminal value in discounted cash flow valuation, many (including those who write the books and teach classes on the topic) presume that there is only way to estimate terminal value and that is to assume that your cash flows grow at a constant rate forever.
          The cash flow and discount rate can be defined in equity terms (as cash flows left over after debt payments and cost of equity) or firm terms (pre-debt cash flows and cost of capital). Not only does that the very notion of "forever" scare some from using DCF but it becomes the cudgel used by DCF skeptics to bash the very notion of a discounted cash flow value.

          In fact, the presumption of there being only one way to estimate the terminal value is wrong. Within the present value framework, there are two simple devices that exist that allow us to make this judgment without breaking the basis for the model.
          1. If it is a finite life asset (say 40 or 50 years), you can use an annuity or growing annuity formula to compute the terminal value. For instance, consider a 40-year asset with the following cash flows:

          Year123456-40
          Cash flow$100 $125 $150 $175 $200 Grows at 2% a year
          The value of this asset, with a risk-adjusted discount rate of 8%, can be written as follows:
          The last term is the present value of the cash flows from years 6 to 40 (35 years of cash flows), with the growing annuity equation delivering a value at the start of year 6, which is also effectively the end of year 5, and the second discounting factor (1.08^5) bringing it back to today. If this asset’s cash flows had lasted forever, growing at 2% a year forever, the last term simplifies further:
          As the life of the asset increases, the value quickly converges to this perpetual value, as shown in the graph below.

          The terminal value (at the end of year 5) is $3,317, with a 65-year life, and $3400, if you assume the asset lasts forever, thus providing an explanation for why we are so cavalier about making the assumption that cash flows grow forever when valuing companies.
          2. There is one other legitimate way of estimating the terminal value in a discounted cash flow valuation and that is to assume that at the end of your forecast period, your business will cease to be a going concern and will liquidate its assets individually. Thus, in the example above, if you assume that the business will be shut down after 5 years and that its assets can be liquidated for $2,000, you could use the liquidation value as your terminal value.
          Faced with the question of whether to use going concern value or liquidation value, it is common sense that dictates the answer. If you are valuing a privately owned restaurant or retail store, with a favorable lease on a prime location, you may decide to value the business over the remaining life of the lease rather than assume a continuing business, simply because a lease renegotiation could very quickly change the economics of the business. Similarly, when valuing a personal services business with an aging owner, you should recognize that the actuarial tables will conflict with the "forever" assumption.

          And One Non-starter: A Trojan Horse DCF
          There is a third way that is used to estimate terminal value that undercuts the notion of intrinsic value, which is what DCF is designed to measure. That is the use of a multiple of some operating metric (revenues, earnings etc.) in your terminal year to get to a terminal value. In almost every case where this is done, the multiple that is used to estimate the terminal value comes from looking at what peer group companies trade at, in the market today. Thus, if telecomm companies collectively trade at a EV/EBITDA multiple of six today, that multiple is used on the EBITDA in year n to arrive at a terminal value.
          That makes he biggest number in your DCF a pricing, and it is for this reason that I labeled these “Trojan Horse” valuations in my post on dysfunctional DCFs. As have argued in multiple posts, there is nothing wrong with pricing a business and that may be what you are asked to do, but if that is the case, you should do a simple pricing and not go through the charade of estimating cash flows and discount rates, giving the patina of an intrinsic value estimate.

          Conclusion
          As in my posts on discount rates, I would like to emphasize that the DCF approach is much more flexible than people give it credit for being. Thus, if your pet peeve with DCFs is the assumption that cash flows last forever and keep growing, it is time to let go of that grievance.  There are other ways of estimating the terminal value that you should be more comfortable with and that you can substitute for the perpetual growth model. The only cautionary note is that using a multiple obtained by looking at what peer group companies introduces an overwhelming pricing element into your intrinsic valuation.

          YouTube Video



          1. If you have a D(discount rate) and a CF (cash flow), you have a DCF.  
          2. A DCF is an exercise in modeling & number crunching. 
          3. You cannot do a DCF when there is too much uncertainty.
          4. It's all about D in the DCF (Myths 4.14.24.34.4 & 4.5)
          5. The Terminal Value: Elephant in the Room! (Myths 5.1, 5.2, 5.3, 5.4 & 5.5)
          6. A DCF requires too many assumptions and can be manipulated to yield any value you want.
          7. A DCF cannot value brand name or other intangibles. 
          8. A DCF yields a conservative estimate of value. 
          9. If your DCF value changes significantly over time, there is something wrong with your valuation.
          10. A DCF is an academic exercise.
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